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lukasmasuch / best-of-ml-python

πŸ† A ranked list of awesome machine learning Python libraries. Updated weekly.

23,241 stars
3,093 forks
34 issues

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<!-- markdownlint-disable --> <h1 align="center"> Best-of Machine Learning with Python <br> </h1> <p align="center"> <strong>πŸ†&nbsp; A ranked list of awesome machine learning Python libraries. Updated weekly.</strong> </p> <p align="center"> <a href="https://github.com/ml-tooling/best-of" title="Best-of-badge"><img src="http://bit.ly/3o3EHNN"></a> <a href="#Contents" title="Project Count"><img src="https://img.shields.io/badge/projects-920-blue.svg?color=5ac4bf"></a> <a href="#Contribution" title="Contributions are welcome"><img src="https://img.shields.io/badge/contributions-welcome-green.svg"></a> <a href="https://github.com/ml-tooling/best-of-ml-python/releases" title="Best-of Updates"><img src="https://img.shields.io/github/release-date/ml-tooling/best-of-ml-python?color=green&label=updated"></a> <a href="https://mltooling.substack.com/subscribe" title="Subscribe to newsletter"><img src="http://bit.ly/2Md9rxM"></a> <a href="https://twitter.com/mltooling" title="Follow on Twitter"><img src="https://img.shields.io/twitter/follow/mltooling.svg?style=social&label=Follow"></a> </p>

This curated list contains 920 awesome open-source projects with a total of 5.1M stars grouped into 34 categories. All projects are ranked by a project-quality score, which is calculated based on various metrics automatically collected from GitHub and different package managers. If you like to add or update projects, feel free to open an issue, submit a pull request, or directly edit the projects.yaml. Contributions are very welcome!


<p align="center"> πŸ§™β€β™‚οΈ&nbsp; Discover other <a href="https://best-of.org">best-of lists</a> or create <a href="https://github.com/best-of-lists/best-of/blob/main/create-best-of-list.md">your own</a>.<br> πŸ“«&nbsp; Subscribe to our <a href="https://mltooling.substack.com/subscribe">newsletter</a> for updates and trending projects. </p>

Contents

Explanation

  • πŸ₯‡πŸ₯ˆπŸ₯‰Β  Combined project-quality score
  • ⭐️  Star count from GitHub
  • 🐣  New project (less than 6 months old)
  • πŸ’€Β  Inactive project (6 months no activity)
  • πŸ’€Β  Dead project (12 months no activity)
  • πŸ“ˆπŸ“‰Β  Project is trending up or down
  • βž•Β  Project was recently added
  • ❗️  Warning (e.g. missing/risky license)
  • πŸ‘¨β€πŸ’»Β  Contributors count from GitHub
  • πŸ”€Β  Fork count from GitHub
  • πŸ“‹Β  Issue count from GitHub
  • ⏱️  Last update timestamp on package manager
  • πŸ“₯Β  Download count from package manager
  • πŸ“¦Β  Number of dependent projects
  • <img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13">Β  Tensorflow related project
  • <img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13">Β  Sklearn related project
  • <img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13">Β  PyTorch related project
  • <img src="https://git.io/JLy1X" style="display:inline;" width="13" height="13">Β  MxNet related project
  • <img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13">Β  Apache Spark related project
  • <img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13">Β  Jupyter related project
  • <img src="https://git.io/JLy1M" style="display:inline;" width="13" height="13">Β  PaddlePaddle related project
  • <img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13">Β  Pandas related project
  • <img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13">Β  Jax related project
<br>

Machine Learning Frameworks

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

General-purpose machine learning and deep learning frameworks.

<details><summary><b><a href="https://github.com/tensorflow/tensorflow">Tensorflow</a></b> (πŸ₯‡56 Β· ⭐ 200K) - An Open Source Machine Learning Framework for Everyone. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 5K Β· πŸ”€ 75K Β· πŸ“¦ 540K Β· πŸ“‹ 42K - 4% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/tensorflow/tensorflow
    
  • PyPi (πŸ“₯ 26M / month Β· πŸ“¦ 9.6K Β· ⏱️ 13.08.2025):

    pip install tensorflow
    
  • Conda (πŸ“₯ 6M Β· ⏱️ 27.10.2025):

    conda install -c conda-forge tensorflow
    
  • Docker Hub (πŸ“₯ 81M Β· ⭐ 2.8K Β· ⏱️ 30.10.2025):

    docker pull tensorflow/tensorflow
    
</details> <details><summary><b><a href="https://github.com/pytorch/pytorch">PyTorch</a></b> (πŸ₯‡56 Β· ⭐ 94K) - Tensors and Dynamic neural networks in Python with strong GPU.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 6K Β· πŸ”€ 26K Β· πŸ“₯ 110K Β· πŸ“¦ 830K Β· πŸ“‹ 56K - 30% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/pytorch/pytorch
    
  • PyPi (πŸ“₯ 70M / month Β· πŸ“¦ 30K Β· ⏱️ 15.10.2025):

    pip install torch
    
  • Conda (πŸ“₯ 29M Β· ⏱️ 25.03.2025):

    conda install -c pytorch pytorch
    
</details> <details><summary><b><a href="https://github.com/scikit-learn/scikit-learn">scikit-learn</a></b> (πŸ₯‡53 Β· ⭐ 64K) - scikit-learn: machine learning in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 3.4K Β· πŸ”€ 26K Β· πŸ“₯ 1.1K Β· πŸ“¦ 1.3M Β· πŸ“‹ 12K - 17% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/scikit-learn/scikit-learn
    
  • PyPi (πŸ“₯ 140M / month Β· πŸ“¦ 35K Β· ⏱️ 09.09.2025):

    pip install scikit-learn
    
  • Conda (πŸ“₯ 40M Β· ⏱️ 09.09.2025):

    conda install -c conda-forge scikit-learn
    
</details> <details><summary><b><a href="https://github.com/keras-team/keras">Keras</a></b> (πŸ₯‡50 Β· ⭐ 64K) - Deep Learning for humans. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 1.4K Β· πŸ”€ 20K Β· πŸ“¦ 300K Β· πŸ“‹ 13K - 2% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/keras-team/keras
    
  • PyPi (πŸ“₯ 19M / month Β· πŸ“¦ 2K Β· ⏱️ 27.10.2025):

    pip install keras
    
  • Conda (πŸ“₯ 4.5M Β· ⏱️ 28.10.2025):

    conda install -c conda-forge keras
    
</details> <details><summary><b><a href="https://github.com/dmlc/xgboost">XGBoost</a></b> (πŸ₯‡46 Β· ⭐ 28K) - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 670 Β· πŸ”€ 8.8K Β· πŸ“₯ 20K Β· πŸ“¦ 170K Β· πŸ“‹ 5.6K - 8% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/dmlc/xgboost
    
  • PyPi (πŸ“₯ 31M / month Β· πŸ“¦ 2.9K Β· ⏱️ 21.10.2025):

    pip install xgboost
    
  • Conda (πŸ“₯ 6.6M Β· ⏱️ 16.09.2025):

    conda install -c conda-forge xgboost
    
</details> <details><summary><b><a href="https://github.com/PaddlePaddle/Paddle">PaddlePaddle</a></b> (πŸ₯‡46 Β· ⭐ 23K) - PArallel Distributed Deep LEarning: Machine Learning.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1M" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 1.5K Β· πŸ”€ 5.9K Β· πŸ“₯ 15K Β· πŸ“¦ 8.8K Β· πŸ“‹ 20K - 8% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/PaddlePaddle/Paddle
    
  • PyPi (πŸ“₯ 1.6M / month Β· πŸ“¦ 280 Β· ⏱️ 30.10.2025):

    pip install paddlepaddle
    
</details> <details><summary><b><a href="https://github.com/jax-ml/jax">jax</a></b> (πŸ₯‡45 Β· ⭐ 34K) - Composable transformations of Python+NumPy programs: differentiate,.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 980 Β· πŸ”€ 3.2K Β· πŸ“¦ 47K Β· πŸ“‹ 6.6K - 24% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/google/jax
    
  • PyPi (πŸ“₯ 12M / month Β· πŸ“¦ 3.1K Β· ⏱️ 15.10.2025):

    pip install jax
    
  • Conda (πŸ“₯ 3.2M Β· ⏱️ 06.10.2025):

    conda install -c conda-forge jaxlib
    
</details> <details><summary><b><a href="https://github.com/Lightning-AI/pytorch-lightning">pytorch-lightning</a></b> (πŸ₯‡45 Β· ⭐ 30K) - Pretrain, finetune ANY AI model of ANY size on 1 or.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 1K Β· πŸ”€ 3.6K Β· πŸ“₯ 15K Β· πŸ“¦ 48K Β· πŸ“‹ 7.4K - 11% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/Lightning-AI/lightning
    
  • PyPi (πŸ“₯ 9.8M / month Β· πŸ“¦ 1.8K Β· ⏱️ 05.09.2025):

    pip install pytorch-lightning
    
  • Conda (πŸ“₯ 1.7M Β· ⏱️ 05.09.2025):

    conda install -c conda-forge pytorch-lightning
    
</details> <details><summary><b><a href="https://github.com/statsmodels/statsmodels">StatsModels</a></b> (πŸ₯‡45 Β· ⭐ 11K) - Statsmodels: statistical modeling and econometrics in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 470 Β· πŸ”€ 3.3K Β· πŸ“₯ 36 Β· πŸ“¦ 180K Β· πŸ“‹ 5.8K - 50% open Β· ⏱️ 22.10.2025):

    git clone https://github.com/statsmodels/statsmodels
    
  • PyPi (πŸ“₯ 24M / month Β· πŸ“¦ 5.6K Β· ⏱️ 07.07.2025):

    pip install statsmodels
    
  • Conda (πŸ“₯ 22M Β· ⏱️ 01.10.2025):

    conda install -c conda-forge statsmodels
    
</details> <details><summary><b><a href="https://github.com/apache/spark">PySpark</a></b> (πŸ₯ˆ44 Β· ⭐ 42K) - Apache Spark Python API. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 3.3K Β· πŸ”€ 29K Β· ⏱️ 30.10.2025):

    git clone https://github.com/apache/spark
    
  • PyPi (πŸ“₯ 47M / month Β· πŸ“¦ 2.1K Β· ⏱️ 30.10.2025):

    pip install pyspark
    
  • Conda (πŸ“₯ 4.2M Β· ⏱️ 08.09.2025):

    conda install -c conda-forge pyspark
    
</details> <details><summary><b><a href="https://github.com/microsoft/LightGBM">LightGBM</a></b> (πŸ₯ˆ42 Β· ⭐ 18K) - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 330 Β· πŸ”€ 3.9K Β· πŸ“₯ 310K Β· πŸ“¦ 56K Β· πŸ“‹ 3.6K - 12% open Β· ⏱️ 28.10.2025):

    git clone https://github.com/microsoft/LightGBM
    
  • PyPi (πŸ“₯ 11M / month Β· πŸ“¦ 1.6K Β· ⏱️ 15.02.2025):

    pip install lightgbm
    
  • Conda (πŸ“₯ 4.1M Β· ⏱️ 20.10.2025):

    conda install -c conda-forge lightgbm
    
</details> <details><summary><b><a href="https://github.com/catboost/catboost">Catboost</a></b> (πŸ₯ˆ42 Β· ⭐ 8.6K) - A fast, scalable, high performance Gradient Boosting on Decision.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 1.4K Β· πŸ”€ 1.2K Β· πŸ“₯ 460K Β· πŸ“¦ 19 Β· πŸ“‹ 2.5K - 25% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/catboost/catboost
    
  • PyPi (πŸ“₯ 5.1M / month Β· πŸ“¦ 650 Β· ⏱️ 13.04.2025):

    pip install catboost
    
  • Conda (πŸ“₯ 2.2M Β· ⏱️ 09.08.2025):

    conda install -c conda-forge catboost
    
</details> <details><summary><b><a href="https://github.com/fastai/fastai">Fastai</a></b> (πŸ₯ˆ41 Β· ⭐ 28K) - The fastai deep learning library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 680 Β· πŸ”€ 7.6K Β· πŸ“¦ 23K Β· πŸ“‹ 1.9K - 14% open Β· ⏱️ 26.10.2025):

    git clone https://github.com/fastai/fastai
    
  • PyPi (πŸ“₯ 640K / month Β· πŸ“¦ 340 Β· ⏱️ 26.10.2025):

    pip install fastai
    
</details> <details><summary><b><a href="https://github.com/apache/flink">PyFlink</a></b> (πŸ₯ˆ39 Β· ⭐ 25K) - Apache Flink Python API. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 2.1K Β· πŸ”€ 14K Β· πŸ“¦ 21 Β· ⏱️ 30.10.2025):

    git clone https://github.com/apache/flink
    
  • PyPi (πŸ“₯ 450K / month Β· πŸ“¦ 38 Β· ⏱️ 28.10.2025):

    pip install apache-flink
    
</details> <details><summary><b><a href="https://github.com/google/flax">Flax</a></b> (πŸ₯ˆ38 Β· ⭐ 6.9K) - Flax is a neural network library for JAX that is designed for.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 280 Β· πŸ”€ 740 Β· πŸ“₯ 61 Β· πŸ“¦ 15K Β· πŸ“‹ 1.3K - 33% open Β· ⏱️ 27.10.2025):

    git clone https://github.com/google/flax
    
  • PyPi (πŸ“₯ 2M / month Β· πŸ“¦ 740 Β· ⏱️ 25.09.2025):

    pip install flax
    
  • Conda (πŸ“₯ 130K Β· ⏱️ 27.10.2025):

    conda install -c conda-forge flax
    
</details> <details><summary><b><a href="https://github.com/pytorch/ignite">Ignite</a></b> (πŸ₯ˆ36 Β· ⭐ 4.7K) - High-level library to help with training and evaluating neural.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 1K Β· πŸ”€ 660 Β· πŸ“¦ 3.9K Β· πŸ“‹ 1.4K - 10% open Β· ⏱️ 16.10.2025):

    git clone https://github.com/pytorch/ignite
    
  • PyPi (πŸ“₯ 170K / month Β· πŸ“¦ 120 Β· ⏱️ 30.10.2025):

    pip install pytorch-ignite
    
  • Conda (πŸ“₯ 250K Β· ⏱️ 16.10.2025):

    conda install -c pytorch ignite
    
</details> <details><summary><b><a href="https://github.com/arogozhnikov/einops">einops</a></b> (πŸ₯ˆ35 Β· ⭐ 9.2K) - Flexible and powerful tensor operations for readable and reliable code.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 380 Β· πŸ“¦ 82K Β· πŸ“‹ 200 - 17% open Β· ⏱️ 12.08.2025):

    git clone https://github.com/arogozhnikov/einops
    
  • PyPi (πŸ“₯ 15M / month Β· πŸ“¦ 2.6K Β· ⏱️ 09.02.2025):

    pip install einops
    
  • Conda (πŸ“₯ 470K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge einops
    
</details> <details><summary><b><a href="https://github.com/ivy-llc/ivy">ivy</a></b> (πŸ₯ˆ34 Β· ⭐ 14K) - Convert Machine Learning Code Between Frameworks. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 1.5K Β· πŸ”€ 5.6K Β· πŸ“‹ 17K - 5% open Β· ⏱️ 10.10.2025):

    git clone https://github.com/unifyai/ivy
    
  • PyPi (πŸ“₯ 33K / month Β· πŸ“¦ 16 Β· ⏱️ 16.06.2025):

    pip install ivy
    
</details> <details><summary><b><a href="https://github.com/jina-ai/serve">Jina</a></b> (πŸ₯ˆ33 Β· ⭐ 22K Β· πŸ’€) - Build multimodal AI applications with cloud-native stack. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 2.2K Β· ⏱️ 24.03.2025):

    git clone https://github.com/jina-ai/jina
    
  • PyPi (πŸ“₯ 120K / month Β· πŸ“¦ 29 Β· ⏱️ 24.03.2025):

    pip install jina
    
  • Conda (πŸ“₯ 110K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge jina-core
    
  • Docker Hub (πŸ“₯ 1.8M Β· ⭐ 9 Β· ⏱️ 24.03.2025):

    docker pull jinaai/jina
    
</details> <details><summary><b><a href="https://github.com/mlpack/mlpack">mlpack</a></b> (πŸ₯ˆ33 Β· ⭐ 5.5K) - mlpack: a fast, header-only C++ machine learning library. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 340 Β· πŸ”€ 1.7K Β· πŸ“‹ 1.7K - 1% open Β· ⏱️ 27.10.2025):

    git clone https://github.com/mlpack/mlpack
    
  • PyPi (πŸ“₯ 4.7K / month Β· πŸ“¦ 6 Β· ⏱️ 22.05.2025):

    pip install mlpack
    
  • Conda (πŸ“₯ 410K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge mlpack
    
</details> <details><summary><b><a href="https://github.com/explosion/thinc">Thinc</a></b> (πŸ₯ˆ33 Β· ⭐ 2.9K Β· πŸ’€) - A refreshing functional take on deep learning, compatible with your.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 67 Β· πŸ”€ 280 Β· πŸ“₯ 2K Β· πŸ“¦ 70K Β· πŸ“‹ 160 - 14% open Β· ⏱️ 07.03.2025):

    git clone https://github.com/explosion/thinc
    
  • PyPi (πŸ“₯ 17M / month Β· πŸ“¦ 160 Β· ⏱️ 04.04.2025):

    pip install thinc
    
  • Conda (πŸ“₯ 3.9M Β· ⏱️ 06.07.2025):

    conda install -c conda-forge thinc
    
</details> <details><summary><b><a href="https://github.com/ludwig-ai/ludwig">Ludwig</a></b> (πŸ₯‰32 Β· ⭐ 12K Β· πŸ’€) - Low-code framework for building custom LLMs, neural networks,.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 1.2K Β· πŸ“¦ 340 Β· πŸ“‹ 1.1K - 4% open Β· ⏱️ 17.10.2024):

    git clone https://github.com/ludwig-ai/ludwig
    
  • PyPi (πŸ“₯ 3.8K / month Β· πŸ“¦ 6 Β· ⏱️ 30.07.2024):

    pip install ludwig
    
</details> <details><summary><b><a href="https://github.com/skorch-dev/skorch">skorch</a></b> (πŸ₯‰32 Β· ⭐ 6.1K) - A scikit-learn compatible neural network library that wraps.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 68 Β· πŸ”€ 400 Β· πŸ“¦ 1.7K Β· πŸ“‹ 540 - 12% open Β· ⏱️ 23.10.2025):

    git clone https://github.com/skorch-dev/skorch
    
  • PyPi (πŸ“₯ 150K / month Β· πŸ“¦ 110 Β· ⏱️ 08.08.2025):

    pip install skorch
    
  • Conda (πŸ“₯ 810K Β· ⏱️ 08.08.2025):

    conda install -c conda-forge skorch
    
</details> <details><summary><b><a href="https://github.com/google-deepmind/sonnet">Sonnet</a></b> (πŸ₯‰31 Β· ⭐ 9.9K) - TensorFlow-based neural network library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 1.3K Β· πŸ“¦ 1.5K Β· πŸ“‹ 190 - 16% open Β· ⏱️ 04.08.2025):

    git clone https://github.com/deepmind/sonnet
    
  • PyPi (πŸ“₯ 35K / month Β· πŸ“¦ 19 Β· ⏱️ 02.01.2024):

    pip install dm-sonnet
    
  • Conda (πŸ“₯ 47K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge sonnet
    
</details> <details><summary><b><a href="https://github.com/google-deepmind/dm-haiku">Haiku</a></b> (πŸ₯‰31 Β· ⭐ 3.1K Β· πŸ“‰) - JAX-based neural network library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 260 Β· πŸ“¦ 2.6K Β· πŸ“‹ 250 - 29% open Β· ⏱️ 29.09.2025):

    git clone https://github.com/deepmind/dm-haiku
    
  • PyPi (πŸ“₯ 260K / month Β· πŸ“¦ 200 Β· ⏱️ 18.09.2025):

    pip install dm-haiku
    
  • Conda (πŸ“₯ 44K Β· ⏱️ 19.09.2025):

    conda install -c conda-forge dm-haiku
    
</details> <details><summary><b><a href="https://github.com/ROCm/tensorflow-upstream">tensorflow-upstream</a></b> (πŸ₯‰31 Β· ⭐ 700) - TensorFlow ROCm port. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 5K Β· πŸ”€ 100 Β· πŸ“₯ 31 Β· πŸ“‹ 400 - 3% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/ROCmSoftwarePlatform/tensorflow-upstream
    
  • PyPi (πŸ“₯ 1.7K / month Β· πŸ“¦ 9 Β· ⏱️ 10.01.2024):

    pip install tensorflow-rocm
    
</details> <details><summary><b><a href="https://github.com/geomstats/geomstats">Geomstats</a></b> (πŸ₯‰30 Β· ⭐ 1.4K) - Computations and statistics on manifolds with geometric structures. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 97 Β· πŸ”€ 260 Β· πŸ“¦ 150 Β· πŸ“‹ 570 - 36% open Β· ⏱️ 06.10.2025):

    git clone https://github.com/geomstats/geomstats
    
  • PyPi (πŸ“₯ 15K / month Β· πŸ“¦ 12 Β· ⏱️ 09.09.2024):

    pip install geomstats
    
  • Conda (πŸ“₯ 8.2K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge geomstats
    
</details> <details><summary><b><a href="https://github.com/pyRiemann/pyRiemann">pyRiemann</a></b> (πŸ₯‰28 Β· ⭐ 700) - Machine learning for multivariate data through the Riemannian.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 170 Β· πŸ“¦ 480 Β· πŸ“‹ 110 - 2% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/pyRiemann/pyRiemann
    
  • PyPi (πŸ“₯ 75K / month Β· πŸ“¦ 31 Β· ⏱️ 23.07.2025):

    pip install pyriemann
    
  • Conda (πŸ“₯ 16K Β· ⏱️ 23.07.2025):

    conda install -c conda-forge pyriemann
    
</details> <details><summary><b><a href="https://github.com/numenta/nupic-legacy">NuPIC</a></b> (πŸ₯‰27 Β· ⭐ 6.4K Β· πŸ’€) - Numenta Platform for Intelligent Computing is an implementation of.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 1.5K Β· πŸ“₯ 26 Β· πŸ“¦ 21 Β· πŸ“‹ 1.8K - 25% open Β· ⏱️ 03.12.2024):

    git clone https://github.com/numenta/nupic
    
  • PyPi (πŸ“₯ 510 / month Β· ⏱️ 01.09.2016):

    pip install nupic
    
</details> <details><summary><b><a href="https://github.com/determined-ai/determined">Determined</a></b> (πŸ₯‰26 Β· ⭐ 3.2K Β· πŸ’€) - Determined is an open-source machine learning.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 360 Β· πŸ“₯ 7.8K Β· πŸ“‹ 450 - 22% open Β· ⏱️ 20.03.2025):

    git clone https://github.com/determined-ai/determined
    
  • PyPi (πŸ“₯ 33K / month Β· πŸ“¦ 4 Β· ⏱️ 19.03.2025):

    pip install determined
    
</details> <details><summary><b><a href="https://github.com/sony/nnabla">Neural Network Libraries</a></b> (πŸ₯‰26 Β· ⭐ 2.8K) - Neural Network Libraries. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 76 Β· πŸ”€ 340 Β· πŸ“₯ 1K Β· πŸ“‹ 95 - 36% open Β· ⏱️ 29.08.2025):

    git clone https://github.com/sony/nnabla
    
  • PyPi (πŸ“₯ 1.6K / month Β· πŸ“¦ 44 Β· ⏱️ 29.05.2024):

    pip install nnabla
    
</details> <details><summary><b><a href="https://github.com/deepinv/deepinv">deepinv</a></b> (πŸ₯‰26 Β· ⭐ 540) - DeepInverse: a PyTorch library for solving imaging inverse problems.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 53 Β· πŸ”€ 120 Β· πŸ“₯ 24 Β· πŸ“¦ 23 Β· πŸ“‹ 350 - 33% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/deepinv/deepinv
    
  • PyPi (πŸ“₯ 2.4K / month Β· ⏱️ 08.10.2025):

    pip install deepinv
    
</details> <details><summary><b><a href="https://github.com/towhee-io/towhee">Towhee</a></b> (πŸ₯‰23 Β· ⭐ 3.4K Β· πŸ’€) - Towhee is a framework that is dedicated to making neural data.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 260 Β· πŸ“₯ 2.7K Β· πŸ“‹ 670 - 0% open Β· ⏱️ 18.10.2024):

    git clone https://github.com/towhee-io/towhee
    
  • PyPi (πŸ“₯ 1.3K / month Β· ⏱️ 04.12.2023):

    pip install towhee
    
</details> <details><summary><b><a href="https://github.com/nubank/fklearn">fklearn</a></b> (πŸ₯‰22 Β· ⭐ 1.5K) - fklearn: Functional Machine Learning. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 170 Β· πŸ“¦ 16 Β· πŸ“‹ 64 - 60% open Β· ⏱️ 23.04.2025):

    git clone https://github.com/nubank/fklearn
    
  • PyPi (πŸ“₯ 750 / month Β· ⏱️ 26.02.2025):

    pip install fklearn
    
</details> <details><summary><b><a href="https://github.com/run-house/kubetorch">Runhouse</a></b> (πŸ₯‰21 Β· ⭐ 1.1K) - Distribute and run AI workloads magically in Python, like PyTorch.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 41 Β· πŸ“₯ 79 Β· ⏱️ 29.10.2025):

    git clone https://github.com/run-house/runhouse
    
  • PyPi (πŸ“₯ 4.5K / month Β· πŸ“¦ 1 Β· ⏱️ 10.03.2025):

    pip install runhouse
    
</details> <details><summary><b><a href="https://github.com/neoml-lib/neoml">NeoML</a></b> (πŸ₯‰19 Β· ⭐ 790) - Machine learning framework for both deep learning and traditional.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 130 Β· πŸ“¦ 2 Β· πŸ“‹ 91 - 40% open Β· ⏱️ 28.10.2025):

    git clone https://github.com/neoml-lib/neoml
    
  • PyPi (πŸ“₯ 190 / month Β· ⏱️ 26.12.2023):

    pip install neoml
    
</details> <details><summary><b><a href="https://github.com/serengil/chefboost">chefboost</a></b> (πŸ₯‰19 Β· ⭐ 480) - A Lightweight Decision Tree Framework supporting regular algorithms:.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 100 Β· πŸ“¦ 72 Β· ⏱️ 09.07.2025):

    git clone https://github.com/serengil/chefboost
    
  • PyPi (πŸ“₯ 770 / month Β· ⏱️ 30.10.2024):

    pip install chefboost
    
</details> <details><summary><b><a href="https://github.com/Xtra-Computing/thundergbm">ThunderGBM</a></b> (πŸ₯‰18 Β· ⭐ 710 Β· πŸ’€) - ThunderGBM: Fast GBDTs and Random Forests on GPUs. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 88 Β· πŸ“¦ 4 Β· πŸ“‹ 81 - 48% open Β· ⏱️ 19.03.2025):

    git clone https://github.com/Xtra-Computing/thundergbm
    
  • PyPi (πŸ“₯ 220 / month Β· ⏱️ 19.09.2022):

    pip install thundergbm
    
</details> <details><summary>Show 26 hidden projects...</summary>
  • <b><a href="https://github.com/davisking/dlib">dlib</a></b> (πŸ₯ˆ40 Β· ⭐ 14K) - A toolkit for making real world machine learning and data analysis.. <code><a href="https://tldrlegal.com/search?q=BSL-1.0">❗️BSL-1.0</a></code>
  • <b><a href="https://github.com/apache/mxnet">MXNet</a></b> (πŸ₯ˆ38 Β· ⭐ 21K Β· πŸ’€) - Lightweight, Portable, Flexible Distributed/Mobile Deep.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1X" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/Theano/Theano">Theano</a></b> (πŸ₯ˆ37 Β· ⭐ 10K Β· πŸ’€) - Theano was a Python library that allows you to define, optimize, and.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/mindsdb/mindsdb">MindsDB</a></b> (πŸ₯ˆ33 Β· ⭐ 37K) - Federated query engine for AI - The only MCP Server youll ever need. <code><a href="https://tldrlegal.com/search?q=ICU">❗️ICU</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/VowpalWabbit/vowpal_wabbit">Vowpal Wabbit</a></b> (πŸ₯ˆ33 Β· ⭐ 8.6K Β· πŸ’€) - Vowpal Wabbit is a machine learning system which pushes the.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/chainer/chainer">Chainer</a></b> (πŸ₯ˆ33 Β· ⭐ 5.9K Β· πŸ’€) - A flexible framework of neural networks for deep learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/apple/turicreate">Turi Create</a></b> (πŸ₯‰32 Β· ⭐ 11K Β· πŸ’€) - Turi Create simplifies the development of custom machine.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/tensorpack/tensorpack">tensorpack</a></b> (πŸ₯‰32 Β· ⭐ 6.3K Β· πŸ’€) - A Neural Net Training Interface on TensorFlow, with.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/tflearn/tflearn">TFlearn</a></b> (πŸ₯‰31 Β· ⭐ 9.6K Β· πŸ’€) - Deep learning library featuring a higher-level API for TensorFlow. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/clab/dynet">dyNET</a></b> (πŸ₯‰31 Β· ⭐ 3.4K Β· πŸ’€) - DyNet: The Dynamic Neural Network Toolkit. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/microsoft/CNTK">CNTK</a></b> (πŸ₯‰29 Β· ⭐ 18K Β· πŸ’€) - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/Lasagne/Lasagne">Lasagne</a></b> (πŸ₯‰28 Β· ⭐ 3.9K Β· πŸ’€) - Lightweight library to build and train neural networks in Theano. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/shogun-toolbox/shogun">SHOGUN</a></b> (πŸ₯‰26 Β· ⭐ 3.1K Β· πŸ’€) - Unified and efficient Machine Learning. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/amaiya/ktrain">ktrain</a></b> (πŸ₯‰26 Β· ⭐ 1.3K Β· πŸ’€) - ktrain is a Python library that makes deep learning and AI.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/itdxer/neupy">NeuPy</a></b> (πŸ₯‰25 Β· ⭐ 740 Β· πŸ’€) - NeuPy is a Tensorflow based python library for prototyping and building.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/aksnzhy/xlearn">xLearn</a></b> (πŸ₯‰24 Β· ⭐ 3.1K Β· πŸ’€) - High performance, easy-to-use, and scalable machine learning (ML).. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/georgia-tech-db/evadb">EvaDB</a></b> (πŸ₯‰24 Β· ⭐ 2.7K Β· πŸ’€) - Database system for AI-powered apps. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/NervanaSystems/neon">neon</a></b> (πŸ₯‰22 Β· ⭐ 3.9K Β· πŸ’€) - Intel Nervana reference deep learning framework committed to best.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/Xtra-Computing/thundersvm">ThunderSVM</a></b> (πŸ₯‰22 Β· ⭐ 1.6K Β· πŸ’€) - ThunderSVM: A Fast SVM Library on GPUs and CPUs. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/pytorchbearer/torchbearer">Torchbearer</a></b> (πŸ₯‰22 Β· ⭐ 640 Β· πŸ’€) - torchbearer: A model fitting library for PyTorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/XiaoMi/mace">mace</a></b> (πŸ₯‰21 Β· ⭐ 5K Β· πŸ’€) - MACE is a deep learning inference framework optimized for mobile.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/google/neural-tangents">Neural Tangents</a></b> (πŸ₯‰21 Β· ⭐ 2.4K Β· πŸ’€) - Fast and Easy Infinite Neural Networks in Python. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/google/objax">Objax</a></b> (πŸ₯‰20 Β· ⭐ 770 Β· πŸ’€) - Objax is a machine learning framework that provides an Object.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/poets-ai/elegy">elegy</a></b> (πŸ₯‰19 Β· ⭐ 480 Β· πŸ’€) - A High Level API for Deep Learning in JAX. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/facebookresearch/StarSpace">StarSpace</a></b> (πŸ₯‰16 Β· ⭐ 4K Β· πŸ’€) - Learning embeddings for classification, retrieval and ranking. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/HenryNdubuaku/nanodl">nanodl</a></b> (πŸ₯‰14 Β· ⭐ 300 Β· πŸ’€) - A Jax-based library for building transformers, includes.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code>
</details> <br>

Data Visualization

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

General-purpose and task-specific data visualization libraries.

<details><summary><b><a href="https://github.com/matplotlib/matplotlib">Matplotlib</a></b> (πŸ₯‡49 Β· ⭐ 22K) - matplotlib: plotting with Python. <code>❗Unlicensed</code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 1.9K Β· πŸ”€ 8.1K Β· πŸ“¦ 1.9M Β· πŸ“‹ 11K - 14% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/matplotlib/matplotlib
    
  • PyPi (πŸ“₯ 120M / month Β· πŸ“¦ 68K Β· ⏱️ 09.10.2025):

    pip install matplotlib
    
  • Conda (πŸ“₯ 33M Β· ⏱️ 15.10.2025):

    conda install -c conda-forge matplotlib
    
</details> <details><summary><b><a href="https://github.com/plotly/plotly.py">Plotly</a></b> (πŸ₯‡47 Β· ⭐ 18K) - The interactive graphing library for Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 300 Β· πŸ”€ 2.7K Β· πŸ“₯ 550 Β· πŸ“¦ 460K Β· πŸ“‹ 3.3K - 21% open Β· ⏱️ 28.10.2025):

    git clone https://github.com/plotly/plotly.py
    
  • PyPi (πŸ“₯ 37M / month Β· πŸ“¦ 9.7K Β· ⏱️ 02.10.2025):

    pip install plotly
    
  • Conda (πŸ“₯ 12M Β· ⏱️ 03.10.2025):

    conda install -c conda-forge plotly
    
  • npm (πŸ“₯ 2.8K / month Β· πŸ“¦ 9 Β· ⏱️ 12.01.2021):

    npm install plotlywidget
    
</details> <details><summary><b><a href="https://github.com/plotly/dash">dash</a></b> (πŸ₯‡45 Β· ⭐ 24K) - Data Apps & Dashboards for Python. No JavaScript Required. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 2.2K Β· πŸ“₯ 120 Β· πŸ“¦ 89K Β· πŸ“‹ 2.1K - 27% open Β· ⏱️ 21.10.2025):

    git clone https://github.com/plotly/dash
    
  • PyPi (πŸ“₯ 5.5M / month Β· πŸ“¦ 1.9K Β· ⏱️ 22.10.2025):

    pip install dash
    
  • Conda (πŸ“₯ 2.1M Β· ⏱️ 11.08.2025):

    conda install -c conda-forge dash
    
</details> <details><summary><b><a href="https://github.com/bokeh/bokeh">Bokeh</a></b> (πŸ₯‡45 Β· ⭐ 20K) - Interactive Data Visualization in the browser, from Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 720 Β· πŸ”€ 4.2K Β· πŸ“¦ 100K Β· πŸ“‹ 8.1K - 10% open Β· ⏱️ 28.10.2025):

    git clone https://github.com/bokeh/bokeh
    
  • PyPi (πŸ“₯ 5M / month Β· πŸ“¦ 2.2K Β· ⏱️ 13.10.2025):

    pip install bokeh
    
  • Conda (πŸ“₯ 18M Β· ⏱️ 30.08.2025):

    conda install -c conda-forge bokeh
    
</details> <details><summary><b><a href="https://github.com/mwaskom/seaborn">Seaborn</a></b> (πŸ₯‡42 Β· ⭐ 14K) - Statistical data visualization in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 220 Β· πŸ”€ 2K Β· πŸ“₯ 510 Β· πŸ“¦ 700K Β· πŸ“‹ 2.6K - 6% open Β· ⏱️ 10.07.2025):

    git clone https://github.com/mwaskom/seaborn
    
  • PyPi (πŸ“₯ 31M / month Β· πŸ“¦ 11K Β· ⏱️ 25.01.2024):

    pip install seaborn
    
  • Conda (πŸ“₯ 15M Β· ⏱️ 22.04.2025):

    conda install -c conda-forge seaborn
    
</details> <details><summary><b><a href="https://github.com/vega/altair">Altair</a></b> (πŸ₯‡41 Β· ⭐ 10K) - Declarative visualization library for Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 800 Β· πŸ“₯ 280 Β· πŸ“¦ 240K Β· πŸ“‹ 2.1K - 6% open Β· ⏱️ 27.10.2025):

    git clone https://github.com/altair-viz/altair
    
  • PyPi (πŸ“₯ 37M / month Β· πŸ“¦ 920 Β· ⏱️ 23.11.2024):

    pip install altair
    
  • Conda (πŸ“₯ 3M Β· ⏱️ 22.04.2025):

    conda install -c conda-forge altair
    
</details> <details><summary><b><a href="https://github.com/voxel51/fiftyone">FiftyOne</a></b> (πŸ₯ˆ39 Β· ⭐ 10K) - Visualize, create, and debug image and video datasets.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 680 Β· πŸ“¦ 1K Β· πŸ“‹ 1.8K - 35% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/voxel51/fiftyone
    
  • PyPi (πŸ“₯ 170K / month Β· πŸ“¦ 36 Β· ⏱️ 20.10.2025):

    pip install fiftyone
    
</details> <details><summary><b><a href="https://github.com/xflr6/graphviz">Graphviz</a></b> (πŸ₯ˆ39 Β· ⭐ 1.8K) - Simple Python interface for Graphviz. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 220 Β· πŸ“¦ 95K Β· πŸ“‹ 190 - 6% open Β· ⏱️ 26.10.2025):

    git clone https://github.com/xflr6/graphviz
    
  • PyPi (πŸ“₯ 26M / month Β· πŸ“¦ 3.2K Β· ⏱️ 15.06.2025):

    pip install graphviz
    
  • Conda (πŸ“₯ 59K Β· ⏱️ 22.04.2025):

    conda install -c anaconda python-graphviz
    
</details> <details><summary><b><a href="https://github.com/pyvista/pyvista">PyVista</a></b> (πŸ₯ˆ38 Β· ⭐ 3.3K) - 3D plotting and mesh analysis through a streamlined interface for.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 590 Β· πŸ“₯ 960 Β· πŸ“¦ 5.2K Β· πŸ“‹ 2K - 35% open Β· ⏱️ 28.10.2025):

    git clone https://github.com/pyvista/pyvista
    
  • PyPi (πŸ“₯ 1M / month Β· πŸ“¦ 820 Β· ⏱️ 26.08.2025):

    pip install pyvista
    
  • Conda (πŸ“₯ 810K Β· ⏱️ 10.10.2025):

    conda install -c conda-forge pyvista
    
</details> <details><summary><b><a href="https://github.com/holoviz/holoviews">HoloViews</a></b> (πŸ₯ˆ38 Β· ⭐ 2.8K) - With Holoviews, your data visualizes itself. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 410 Β· πŸ“¦ 17K Β· πŸ“‹ 3.4K - 31% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/holoviz/holoviews
    
  • PyPi (πŸ“₯ 820K / month Β· πŸ“¦ 490 Β· ⏱️ 29.10.2025):

    pip install holoviews
    
  • Conda (πŸ“₯ 2.4M Β· ⏱️ 25.06.2025):

    conda install -c conda-forge holoviews
    
  • npm (πŸ“₯ 380 / month Β· πŸ“¦ 7 Β· ⏱️ 20.06.2025):

    npm install @pyviz/jupyterlab_pyviz
    
</details> <details><summary><b><a href="https://github.com/pyecharts/pyecharts">pyecharts</a></b> (πŸ₯ˆ37 Β· ⭐ 16K) - Python Echarts Plotting Library. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 2.9K Β· πŸ“₯ 75 Β· πŸ“¦ 5.5K Β· πŸ“‹ 1.9K - 0% open Β· ⏱️ 10.10.2025):

    git clone https://github.com/pyecharts/pyecharts
    
  • PyPi (πŸ“₯ 530K / month Β· πŸ“¦ 280 Β· ⏱️ 10.10.2025):

    pip install pyecharts
    
</details> <details><summary><b><a href="https://github.com/pyqtgraph/pyqtgraph">PyQtGraph</a></b> (πŸ₯ˆ37 Β· ⭐ 4.2K) - Fast data visualization and GUI tools for scientific / engineering.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 300 Β· πŸ”€ 1.1K Β· πŸ“¦ 13K Β· πŸ“‹ 1.4K - 31% open Β· ⏱️ 02.10.2025):

    git clone https://github.com/pyqtgraph/pyqtgraph
    
  • PyPi (πŸ“₯ 560K / month Β· πŸ“¦ 1K Β· ⏱️ 29.04.2024):

    pip install pyqtgraph
    
  • Conda (πŸ“₯ 880K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge pyqtgraph
    
</details> <details><summary><b><a href="https://github.com/ydataai/ydata-profiling">pandas-profiling</a></b> (πŸ₯ˆ35 Β· ⭐ 13K) - 1 Line of code data quality profiling & exploratory.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.7K Β· πŸ“₯ 490 Β· πŸ“¦ 6.9K Β· πŸ“‹ 850 - 30% open Β· ⏱️ 19.09.2025):

    git clone https://github.com/ydataai/pandas-profiling
    
  • PyPi (πŸ“₯ 330K / month Β· πŸ“¦ 180 Β· ⏱️ 03.02.2023):

    pip install pandas-profiling
    
  • Conda (πŸ“₯ 590K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge pandas-profiling
    
</details> <details><summary><b><a href="https://github.com/has2k1/plotnine">plotnine</a></b> (πŸ₯ˆ35 Β· ⭐ 4.4K) - A Grammar of Graphics for Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 240 Β· πŸ“¦ 13K Β· πŸ“‹ 750 - 10% open Β· ⏱️ 16.10.2025):

    git clone https://github.com/has2k1/plotnine
    
  • PyPi (πŸ“₯ 2.2M / month Β· πŸ“¦ 400 Β· ⏱️ 15.07.2025):

    pip install plotnine
    
  • Conda (πŸ“₯ 560K Β· ⏱️ 15.07.2025):

    conda install -c conda-forge plotnine
    
</details> <details><summary><b><a href="https://github.com/SciTools/cartopy">cartopy</a></b> (πŸ₯ˆ35 Β· ⭐ 1.5K) - Cartopy - a cartographic python library with matplotlib support. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 390 Β· πŸ“¦ 8.1K Β· πŸ“‹ 1.3K - 23% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/SciTools/cartopy
    
  • PyPi (πŸ“₯ 810K / month Β· πŸ“¦ 970 Β· ⏱️ 01.08.2025):

    pip install cartopy
    
  • Conda (πŸ“₯ 5.6M Β· ⏱️ 27.10.2025):

    conda install -c conda-forge cartopy
    
</details> <details><summary><b><a href="https://github.com/vispy/vispy">VisPy</a></b> (πŸ₯ˆ34 Β· ⭐ 3.5K Β· πŸ“‰) - High-performance interactive 2D/3D data visualization library. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 210 Β· πŸ”€ 620 Β· πŸ“¦ 2.1K Β· πŸ“‹ 1.5K - 25% open Β· ⏱️ 13.10.2025):

    git clone https://github.com/vispy/vispy
    
  • PyPi (πŸ“₯ 190K / month Β· πŸ“¦ 200 Β· ⏱️ 19.05.2025):

    pip install vispy
    
  • Conda (πŸ“₯ 980K Β· ⏱️ 30.08.2025):

    conda install -c conda-forge vispy
    
  • npm (πŸ“₯ 12 / month Β· πŸ“¦ 3 Β· ⏱️ 15.03.2020):

    npm install vispy
    
</details> <details><summary><b><a href="https://github.com/holoviz/datashader">datashader</a></b> (πŸ₯ˆ34 Β· ⭐ 3.5K) - Quickly and accurately render even the largest data. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 63 Β· πŸ”€ 380 Β· πŸ“¦ 6.3K Β· πŸ“‹ 620 - 24% open Β· ⏱️ 09.10.2025):

    git clone https://github.com/holoviz/datashader
    
  • PyPi (πŸ“₯ 280K / month Β· πŸ“¦ 250 Β· ⏱️ 05.08.2025):

    pip install datashader
    
  • Conda (πŸ“₯ 1.6M Β· ⏱️ 05.08.2025):

    conda install -c conda-forge datashader
    
</details> <details><summary><b><a href="https://github.com/JetBrains/lets-plot">lets-plot</a></b> (πŸ₯ˆ34 Β· ⭐ 1.7K) - Multiplatform plotting library based on the Grammar of Graphics. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 54 Β· πŸ“₯ 3.4K Β· πŸ“¦ 190 Β· πŸ“‹ 740 - 21% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/JetBrains/lets-plot
    
  • PyPi (πŸ“₯ 120K / month Β· πŸ“¦ 16 Β· ⏱️ 12.09.2025):

    pip install lets-plot
    
</details> <details><summary><b><a href="https://github.com/amueller/word_cloud">wordcloud</a></b> (πŸ₯ˆ33 Β· ⭐ 10K) - A little word cloud generator in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 75 Β· πŸ”€ 2.3K Β· πŸ“¦ 21 Β· πŸ“‹ 560 - 24% open Β· ⏱️ 31.08.2025):

    git clone https://github.com/amueller/word_cloud
    
  • PyPi (πŸ“₯ 2M / month Β· πŸ“¦ 550 Β· ⏱️ 10.11.2024):

    pip install wordcloud
    
  • Conda (πŸ“₯ 790K Β· ⏱️ 03.09.2025):

    conda install -c conda-forge wordcloud
    
</details> <details><summary><b><a href="https://github.com/perspective-dev/perspective">Perspective</a></b> (πŸ₯ˆ33 Β· ⭐ 9.5K) - A data visualization and analytics component, especially.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 1.2K Β· πŸ“₯ 12K Β· πŸ“¦ 190 Β· πŸ“‹ 890 - 12% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/finos/perspective
    
  • PyPi (πŸ“₯ 17K / month Β· πŸ“¦ 31 Β· ⏱️ 28.10.2025):

    pip install perspective-python
    
  • Conda (πŸ“₯ 2.4M Β· ⏱️ 28.10.2025):

    conda install -c conda-forge perspective
    
  • npm (πŸ“₯ 600 / month Β· πŸ“¦ 6 Β· ⏱️ 03.09.2025):

    npm install @finos/perspective-jupyterlab
    
</details> <details><summary><b><a href="https://github.com/lmcinnes/umap">UMAP</a></b> (πŸ₯ˆ33 Β· ⭐ 8K) - Uniform Manifold Approximation and Projection. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 850 Β· πŸ“¦ 1 Β· πŸ“‹ 860 - 59% open Β· ⏱️ 26.10.2025):

    git clone https://github.com/lmcinnes/umap
    
  • PyPi (πŸ“₯ 2.7M / month Β· πŸ“¦ 1.3K Β· ⏱️ 03.07.2025):

    pip install umap-learn
    
  • Conda (πŸ“₯ 3.2M Β· ⏱️ 03.07.2025):

    conda install -c conda-forge umap-learn
    
</details> <details><summary><b><a href="https://github.com/holoviz/hvplot">hvPlot</a></b> (πŸ₯ˆ32 Β· ⭐ 1.3K) - A high-level plotting API for pandas, dask, xarray, and networkx built.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 52 Β· πŸ”€ 110 Β· πŸ“¦ 7.3K Β· πŸ“‹ 940 - 41% open Β· ⏱️ 24.10.2025):

    git clone https://github.com/holoviz/hvplot
    
  • PyPi (πŸ“₯ 310K / month Β· πŸ“¦ 270 Β· ⏱️ 29.08.2025):

    pip install hvplot
    
  • Conda (πŸ“₯ 860K Β· ⏱️ 04.09.2025):

    conda install -c conda-forge hvplot
    
</details> <details><summary><b><a href="https://github.com/mpld3/mpld3">mpld3</a></b> (πŸ₯‰31 Β· ⭐ 2.4K Β· πŸ“‰) - An interactive data visualization tool which brings matplotlib.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 54 Β· πŸ”€ 360 Β· πŸ“¦ 7.6K Β· πŸ“‹ 370 - 59% open Β· ⏱️ 27.07.2025):

    git clone https://github.com/mpld3/mpld3
    
  • PyPi (πŸ“₯ 440K / month Β· πŸ“¦ 160 Β· ⏱️ 27.07.2025):

    pip install mpld3
    
  • Conda (πŸ“₯ 280K Β· ⏱️ 28.07.2025):

    conda install -c conda-forge mpld3
    
  • npm (πŸ“₯ 900 / month Β· πŸ“¦ 11 Β· ⏱️ 27.07.2025):

    npm install mpld3
    
</details> <details><summary><b><a href="https://github.com/bqplot/bqplot">bqplot</a></b> (πŸ₯‰30 Β· ⭐ 3.7K) - Plotting library for IPython/Jupyter notebooks. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 66 Β· πŸ”€ 480 Β· πŸ“¦ 62 Β· πŸ“‹ 650 - 42% open Β· ⏱️ 25.08.2025):

    git clone https://github.com/bqplot/bqplot
    
  • PyPi (πŸ“₯ 230K / month Β· πŸ“¦ 110 Β· ⏱️ 21.05.2025):

    pip install bqplot
    
  • Conda (πŸ“₯ 1.9M Β· ⏱️ 02.09.2025):

    conda install -c conda-forge bqplot
    
  • npm (πŸ“₯ 3K / month Β· πŸ“¦ 21 Β· ⏱️ 03.09.2025):

    npm install bqplot
    
</details> <details><summary><b><a href="https://github.com/man-group/dtale">D-Tale</a></b> (πŸ₯‰29 Β· ⭐ 5K) - Visualizer for pandas data structures. <code><a href="https://tldrlegal.com/search?q=LGPL-2.1">❗️LGPL-2.1</a></code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 430 Β· πŸ“¦ 1.5K Β· πŸ“‹ 610 - 10% open Β· ⏱️ 30.07.2025):

    git clone https://github.com/man-group/dtale
    
  • PyPi (πŸ“₯ 31K / month Β· πŸ“¦ 53 Β· ⏱️ 30.07.2025):

    pip install dtale
    
  • Conda (πŸ“₯ 480K Β· ⏱️ 30.07.2025):

    conda install -c conda-forge dtale
    
</details> <details><summary><b><a href="https://github.com/pavlin-policar/openTSNE">openTSNE</a></b> (πŸ₯‰29 Β· ⭐ 1.6K Β· πŸ“ˆ) - Extensible, parallel implementations of t-SNE. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 170 Β· πŸ“¦ 1.1K Β· πŸ“‹ 150 - 2% open Β· ⏱️ 27.10.2025):

    git clone https://github.com/pavlin-policar/openTSNE
    
  • PyPi (πŸ“₯ 58K / month Β· πŸ“¦ 69 Β· ⏱️ 27.10.2025):

    pip install opentsne
    
  • Conda (πŸ“₯ 500K Β· ⏱️ 27.10.2025):

    conda install -c conda-forge opentsne
    
</details> <details><summary><b><a href="https://github.com/predict-idlab/plotly-resampler">Plotly-Resampler</a></b> (πŸ₯‰27 Β· ⭐ 1.2K) - Visualize large time series data with plotly.py. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 74 Β· πŸ“¦ 2K Β· πŸ“‹ 190 - 32% open Β· ⏱️ 03.09.2025):

    git clone https://github.com/predict-idlab/plotly-resampler
    
  • PyPi (πŸ“₯ 370K / month Β· πŸ“¦ 38 Β· ⏱️ 29.08.2025):

    pip install plotly-resampler
    
  • Conda (πŸ“₯ 140K Β· ⏱️ 09.10.2025):

    conda install -c conda-forge plotly-resampler
    
</details> <details><summary><b><a href="https://github.com/ContextLab/hypertools">HyperTools</a></b> (πŸ₯‰26 Β· ⭐ 1.9K) - A Python toolbox for gaining geometric insights into high-dimensional.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 160 Β· πŸ“₯ 73 Β· πŸ“¦ 510 Β· πŸ“‹ 200 - 34% open Β· ⏱️ 10.07.2025):

    git clone https://github.com/ContextLab/hypertools
    
  • PyPi (πŸ“₯ 1.1K / month Β· πŸ“¦ 2 Β· ⏱️ 09.07.2025):

    pip install hypertools
    
</details> <details><summary><b><a href="https://github.com/tensorflow/data-validation">data-validation</a></b> (πŸ₯‰25 Β· ⭐ 780) - Library for exploring and validating machine learning.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 180 Β· πŸ“₯ 1K Β· πŸ“‹ 190 - 20% open Β· ⏱️ 23.06.2025):

    git clone https://github.com/tensorflow/data-validation
    
  • PyPi (πŸ“₯ 150K / month Β· πŸ“¦ 32 Β· ⏱️ 09.06.2025):

    pip install tensorflow-data-validation
    
</details> <details><summary><b><a href="https://github.com/spotify/chartify">Chartify</a></b> (πŸ₯‰24 Β· ⭐ 3.6K Β· πŸ’€) - Python library that makes it easy for data scientists to create.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 340 Β· πŸ“¦ 83 Β· πŸ“‹ 86 - 62% open Β· ⏱️ 16.10.2024):

    git clone https://github.com/spotify/chartify
    
  • PyPi (πŸ“₯ 1.2K / month Β· πŸ“¦ 9 Β· ⏱️ 16.10.2024):

    pip install chartify
    
  • Conda (πŸ“₯ 40K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge chartify
    
</details> <details><summary><b><a href="https://github.com/ing-bank/popmon">Popmon</a></b> (πŸ₯‰22 Β· ⭐ 510) - Monitor the stability of a Pandas or Spark dataframe. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 36 Β· πŸ“₯ 280 Β· πŸ“¦ 22 Β· πŸ“‹ 57 - 28% open Β· ⏱️ 04.09.2025):

    git clone https://github.com/ing-bank/popmon
    
  • PyPi (πŸ“₯ 3.4K / month Β· πŸ“¦ 4 Β· ⏱️ 04.09.2025):

    pip install popmon
    
</details> <details><summary><b><a href="https://github.com/vega/ipyvega">vega</a></b> (πŸ₯‰22 Β· ⭐ 390 Β· πŸ’€) - IPython/Jupyter notebook module for Vega and Vega-Lite. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 65 Β· πŸ“¦ 4 Β· πŸ“‹ 110 - 14% open Β· ⏱️ 01.01.2025):

    git clone https://github.com/vega/ipyvega
    
  • PyPi (πŸ“₯ 26K / month Β· πŸ“¦ 17 Β· ⏱️ 25.09.2024):

    pip install vega
    
  • Conda (πŸ“₯ 940K Β· ⏱️ 04.10.2025):

    conda install -c conda-forge vega
    
</details> <details><summary><b><a href="https://github.com/vega/vegafusion">vegafusion</a></b> (πŸ₯‰21 Β· ⭐ 390) - Serverside scaling for Vega and Altair visualizations. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 26 Β· πŸ“₯ 6.6K Β· πŸ“‹ 150 - 36% open Β· ⏱️ 29.09.2025):

    git clone https://github.com/vegafusion/vegafusion
    
  • PyPi (πŸ“₯ 770 / month Β· πŸ“¦ 2 Β· ⏱️ 09.05.2024):

    pip install vegafusion-jupyter
    
  • Conda (πŸ“₯ 520K Β· ⏱️ 27.10.2025):

    conda install -c conda-forge vegafusion-python-embed
    
  • npm (πŸ“₯ 1.9K / month Β· πŸ“¦ 3 Β· ⏱️ 09.05.2024):

    npm install vegafusion-jupyter
    
</details> <details><summary>Show 22 hidden projects...</summary>
  • <b><a href="https://github.com/ResidentMario/missingno">missingno</a></b> (πŸ₯‰30 Β· ⭐ 4.2K Β· πŸ’€) - Missing data visualization module for Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/PAIR-code/facets">Facets Overview</a></b> (πŸ₯‰28 Β· ⭐ 7.4K Β· πŸ’€) - Visualizations for machine learning datasets. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/santosjorge/cufflinks">Cufflinks</a></b> (πŸ₯‰28 Β· ⭐ 3.1K Β· πŸ’€) - Productivity Tools for Plotly + Pandas. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/jupyter-widgets/pythreejs">pythreejs</a></b> (πŸ₯‰27 Β· ⭐ 980 Β· πŸ’€) - A Jupyter - Three.js bridge. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/fbdesignpro/sweetviz">Sweetviz</a></b> (πŸ₯‰26 Β· ⭐ 3.1K Β· πŸ’€) - Visualize and compare datasets, target values and associations, with.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/AutoViML/AutoViz">AutoViz</a></b> (πŸ₯‰26 Β· ⭐ 1.9K Β· πŸ’€) - Automatically Visualize any dataset, any size with a single line.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/tpvasconcelos/ridgeplot">ridgeplot</a></b> (πŸ₯‰26 Β· ⭐ 240) - Beautiful ridgeline plots in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/adamerose/PandasGUI">PandasGUI</a></b> (πŸ₯‰24 Β· ⭐ 3.3K) - A GUI for Pandas DataFrames. <code><a href="https://tldrlegal.com/search?q=MIT-0">❗️MIT-0</a></code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/facebookresearch/hiplot">HiPlot</a></b> (πŸ₯‰24 Β· ⭐ 2.8K Β· πŸ’€) - HiPlot makes understanding high dimensional data easy. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/marcharper/python-ternary">python-ternary</a></b> (πŸ₯‰24 Β· ⭐ 770 Β· πŸ’€) - Ternary plotting library for python with matplotlib. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/DmitryUlyanov/Multicore-TSNE">Multicore-TSNE</a></b> (πŸ₯‰23 Β· ⭐ 1.9K Β· πŸ’€) - Parallel t-SNE implementation with Python and Torch.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/PatrikHlobil/Pandas-Bokeh">Pandas-Bokeh</a></b> (πŸ₯‰22 Β· ⭐ 890 Β· πŸ’€) - Bokeh Plotting Backend for Pandas and GeoPandas. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/nicolaskruchten/jupyter_pivottablejs">pivottablejs</a></b> (πŸ₯‰21 Β· ⭐ 710 Β· πŸ’€) - Dragndrop Pivot Tables and Charts for Jupyter/IPython.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/leotac/joypy">joypy</a></b> (πŸ₯‰21 Β· ⭐ 600 Β· πŸ’€) - Joyplots in Python with matplotlib & pandas. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/gyli/PyWaffle">PyWaffle</a></b> (πŸ₯‰21 Β· ⭐ 600 Β· πŸ’€) - Make Waffle Charts in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/sosuneko/PDPbox">PDPbox</a></b> (πŸ₯‰20 Β· ⭐ 860 Β· πŸ’€) - python partial dependence plot toolbox. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/t-makaro/animatplot">animatplot</a></b> (πŸ₯‰18 Β· ⭐ 410 Β· πŸ’€) - A python package for animating plots build on matplotlib. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/beringresearch/ivis">ivis</a></b> (πŸ₯‰18 Β· ⭐ 340 Β· πŸ’€) - Dimensionality reduction in very large datasets using Siamese.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/altair-viz/pdvega">pdvega</a></b> (πŸ₯‰16 Β· ⭐ 340 Β· πŸ’€) - Interactive plotting for Pandas using Vega-Lite. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/Zsailer/nx_altair">nx-altair</a></b> (πŸ₯‰16 Β· ⭐ 230 Β· πŸ’€) - Draw interactive NetworkX graphs with Altair. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/data-describe/data-describe">data-describe</a></b> (πŸ₯‰15 Β· ⭐ 300 Β· πŸ’€) - datadescribe: Pythonic EDA Accelerator for Data Science. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/biovault/nptsne">nptsne</a></b> (πŸ₯‰11 Β· ⭐ 33 Β· πŸ’€) - nptsne is a numpy compatible python binary package that offers a.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
</details> <br>

Text Data & NLP

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries for processing, cleaning, manipulating, and analyzing text data as well as libraries for NLP tasks such as language detection, fuzzy matching, classification, seq2seq learning, conversational AI, keyword extraction, and translation.

<details><summary><b><a href="https://github.com/huggingface/transformers">transformers</a></b> (πŸ₯‡54 Β· ⭐ 150K) - Transformers: the model-definition framework for.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 3.6K Β· πŸ”€ 31K Β· πŸ“¦ 400K Β· πŸ“‹ 19K - 11% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/huggingface/transformers
    
  • PyPi (πŸ“₯ 93M / month Β· πŸ“¦ 11K Β· ⏱️ 14.10.2025):

    pip install transformers
    
  • Conda (πŸ“₯ 3.3M Β· ⏱️ 14.10.2025):

    conda install -c conda-forge transformers
    
</details> <details><summary><b><a href="https://github.com/nltk/nltk">nltk</a></b> (πŸ₯‡47 Β· ⭐ 14K) - Suite of libraries and programs for symbolic and statistical natural.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 480 Β· πŸ”€ 3K Β· πŸ“¦ 410K Β· πŸ“‹ 1.9K - 14% open Β· ⏱️ 22.10.2025):

    git clone https://github.com/nltk/nltk
    
  • PyPi (πŸ“₯ 42M / month Β· πŸ“¦ 6.3K Β· ⏱️ 01.10.2025):

    pip install nltk
    
  • Conda (πŸ“₯ 3.4M Β· ⏱️ 01.10.2025):

    conda install -c conda-forge nltk
    
</details> <details><summary><b><a href="https://github.com/BerriAI/litellm">litellm</a></b> (πŸ₯‡45 Β· ⭐ 30K Β· πŸ“‰) - Python SDK, Proxy Server (LLM Gateway) to call 100+.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code>o</code> <code>t</code> <code>h</code> <code>e</code> <code>r</code> <code>s</code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 960 Β· πŸ”€ 4.5K Β· πŸ“₯ 800 Β· πŸ“¦ 17K Β· πŸ“‹ 7.8K - 17% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/BerriAI/litellm
    
  • PyPi (πŸ“₯ 34M / month Β· πŸ“¦ 1.9K Β· ⏱️ 29.10.2025):

    pip install litellm
    
</details> <details><summary><b><a href="https://github.com/explosion/spaCy">spaCy</a></b> (πŸ₯‡43 Β· ⭐ 33K Β· πŸ“ˆ) - Industrial-strength Natural Language Processing (NLP) in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 780 Β· πŸ”€ 4.5K Β· πŸ“₯ 4.9K Β· πŸ“¦ 140K Β· πŸ“‹ 5.8K - 3% open Β· ⏱️ 28.10.2025):

    git clone https://github.com/explosion/spaCy
    
  • PyPi (πŸ“₯ 17M / month Β· πŸ“¦ 3.2K Β· ⏱️ 23.05.2025):

    pip install spacy
    
  • Conda (πŸ“₯ 6.5M Β· ⏱️ 06.07.2025):

    conda install -c conda-forge spacy
    
</details> <details><summary><b><a href="https://github.com/huggingface/sentence-transformers">sentence-transformers</a></b> (πŸ₯‡42 Β· ⭐ 18K) - State-of-the-Art Text Embeddings. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 2.7K Β· πŸ“¦ 120K Β· πŸ“‹ 2.5K - 51% open Β· ⏱️ 22.10.2025):

    git clone https://github.com/UKPLab/sentence-transformers
    
  • PyPi (πŸ“₯ 17M / month Β· πŸ“¦ 3.7K Β· ⏱️ 22.10.2025):

    pip install sentence-transformers
    
  • Conda (πŸ“₯ 1M Β· ⏱️ 22.10.2025):

    conda install -c conda-forge sentence-transformers
    
</details> <details><summary><b><a href="https://github.com/piskvorky/gensim">gensim</a></b> (πŸ₯‡42 Β· ⭐ 16K) - Topic Modelling for Humans. <code><a href="https://tldrlegal.com/search?q=LGPL-2.1">❗️LGPL-2.1</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 460 Β· πŸ”€ 4.4K Β· πŸ“₯ 6.4K Β· πŸ“¦ 78K Β· πŸ“‹ 1.9K - 21% open Β· ⏱️ 16.10.2025):

    git clone https://github.com/RaRe-Technologies/gensim
    
  • PyPi (πŸ“₯ 5.2M / month Β· πŸ“¦ 1.6K Β· ⏱️ 18.10.2025):

    pip install gensim
    
  • Conda (πŸ“₯ 1.8M Β· ⏱️ 22.04.2025):

    conda install -c conda-forge gensim
    
</details> <details><summary><b><a href="https://github.com/google/sentencepiece">sentencepiece</a></b> (πŸ₯‡42 Β· ⭐ 11K) - Unsupervised text tokenizer for Neural Network-based text.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 1.3K Β· πŸ“₯ 110K Β· πŸ“¦ 120K Β· πŸ“‹ 800 - 3% open Β· ⏱️ 04.10.2025):

    git clone https://github.com/google/sentencepiece
    
  • PyPi (πŸ“₯ 31M / month Β· πŸ“¦ 2.4K Β· ⏱️ 12.08.2025):

    pip install sentencepiece
    
  • Conda (πŸ“₯ 1.7M Β· ⏱️ 22.09.2025):

    conda install -c conda-forge sentencepiece
    
</details> <details><summary><b><a href="https://github.com/huggingface/tokenizers">Tokenizers</a></b> (πŸ₯‡40 Β· ⭐ 10K) - Fast State-of-the-Art Tokenizers optimized for Research and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 970 Β· πŸ“₯ 86 Β· πŸ“¦ 180K Β· πŸ“‹ 1.1K - 9% open Β· ⏱️ 16.10.2025):

    git clone https://github.com/huggingface/tokenizers
    
  • PyPi (πŸ“₯ 81M / month Β· πŸ“¦ 1.7K Β· ⏱️ 19.09.2025):

    pip install tokenizers
    
  • Conda (πŸ“₯ 3.6M Β· ⏱️ 19.09.2025):

    conda install -c conda-forge tokenizers
    
</details> <details><summary><b><a href="https://github.com/NVIDIA-NeMo/NeMo">NeMo</a></b> (πŸ₯‡38 Β· ⭐ 16K) - A scalable generative AI framework built for researchers and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 460 Β· πŸ”€ 3.2K Β· πŸ“₯ 520K Β· πŸ“¦ 21 Β· πŸ“‹ 2.8K - 4% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/NVIDIA/NeMo
    
  • PyPi (πŸ“₯ 810K / month Β· πŸ“¦ 18 Β· ⏱️ 27.10.2025):

    pip install nemo-toolkit
    
</details> <details><summary><b><a href="https://github.com/deepset-ai/haystack">haystack</a></b> (πŸ₯‡37 Β· ⭐ 23K) - AI orchestration framework to build customizable, production-ready.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 310 Β· πŸ”€ 2.5K Β· πŸ“¦ 1.3K Β· πŸ“‹ 4.1K - 2% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/deepset-ai/haystack
    
  • PyPi (πŸ“₯ 7.4K / month Β· πŸ“¦ 5 Β· ⏱️ 15.12.2021):

    pip install haystack
    
</details> <details><summary><b><a href="https://github.com/comet-ml/opik">Opik</a></b> (πŸ₯‡37 Β· ⭐ 15K) - Debug, evaluate, and monitor your LLM applications, RAG systems, and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 81 Β· πŸ”€ 1.1K Β· πŸ“¦ 17 Β· πŸ“‹ 540 - 29% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/comet-ml/opik
    
  • PyPi (πŸ“₯ 850K / month Β· πŸ“¦ 34 Β· ⏱️ 29.10.2025):

    pip install opik
    
</details> <details><summary><b><a href="https://github.com/gunthercox/ChatterBot">ChatterBot</a></b> (πŸ₯‡37 Β· ⭐ 14K) - ChatterBot is a machine learning, conversational dialog engine for.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 4.5K Β· πŸ“¦ 6.5K Β· πŸ“‹ 1.7K - 6% open Β· ⏱️ 25.10.2025):

    git clone https://github.com/gunthercox/ChatterBot
    
  • PyPi (πŸ“₯ 20K / month Β· πŸ“¦ 19 Β· ⏱️ 16.10.2025):

    pip install chatterbot
    
</details> <details><summary><b><a href="https://github.com/flairNLP/flair">flair</a></b> (πŸ₯‡37 Β· ⭐ 14K) - A very simple framework for state-of-the-art Natural Language Processing.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 280 Β· πŸ”€ 2.1K Β· πŸ“¦ 4.1K Β· πŸ“‹ 2.4K - 1% open Β· ⏱️ 12.06.2025):

    git clone https://github.com/flairNLP/flair
    
  • PyPi (πŸ“₯ 180K / month Β· πŸ“¦ 160 Β· ⏱️ 05.02.2025):

    pip install flair
    
  • Conda (πŸ“₯ 49K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge python-flair
    
</details> <details><summary><b><a href="https://github.com/sloria/TextBlob">TextBlob</a></b> (πŸ₯‡37 Β· ⭐ 9.5K) - Simple, Pythonic, text processing--Sentiment analysis, part-of-speech.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 37 Β· πŸ”€ 1.2K Β· πŸ“₯ 140 Β· πŸ“¦ 60K Β· πŸ“‹ 280 - 25% open Β· ⏱️ 18.10.2025):

    git clone https://github.com/sloria/TextBlob
    
  • PyPi (πŸ“₯ 1.5M / month Β· πŸ“¦ 400 Β· ⏱️ 13.01.2025):

    pip install textblob
    
  • Conda (πŸ“₯ 340K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge textblob
    
</details> <details><summary><b><a href="https://github.com/facebookresearch/fairseq">fairseq</a></b> (πŸ₯ˆ36 Β· ⭐ 32K) - Facebook AI Research Sequence-to-Sequence Toolkit written in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 430 Β· πŸ”€ 6.6K Β· πŸ“₯ 440 Β· πŸ“¦ 4.4K Β· πŸ“‹ 4.4K - 30% open Β· ⏱️ 30.09.2025):

    git clone https://github.com/facebookresearch/fairseq
    
  • PyPi (πŸ“₯ 77K / month Β· πŸ“¦ 120 Β· ⏱️ 27.06.2022):

    pip install fairseq
    
  • Conda (πŸ“₯ 170K Β· ⏱️ 02.10.2025):

    conda install -c conda-forge fairseq
    
</details> <details><summary><b><a href="https://github.com/stanfordnlp/stanza">stanza</a></b> (πŸ₯ˆ36 Β· ⭐ 7.6K) - Stanford NLP Python library for tokenization, sentence segmentation,.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 72 Β· πŸ”€ 920 Β· πŸ“¦ 4.1K Β· πŸ“‹ 950 - 10% open Β· ⏱️ 05.10.2025):

    git clone https://github.com/stanfordnlp/stanza
    
  • PyPi (πŸ“₯ 770K / month Β· πŸ“¦ 240 Β· ⏱️ 05.10.2025):

    pip install stanza
    
  • Conda (πŸ“₯ 9K Β· ⏱️ 25.03.2025):

    conda install -c stanfordnlp stanza
    
</details> <details><summary><b><a href="https://github.com/qdrant/qdrant">qdrant</a></b> (πŸ₯ˆ35 Β· ⭐ 27K) - Qdrant - High-performance, massive-scale Vector Database and Vector.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.9K Β· πŸ“₯ 500K Β· πŸ“¦ 120 Β· πŸ“‹ 1.6K - 22% open Β· ⏱️ 30.09.2025):

    git clone https://github.com/qdrant/qdrant
    
</details> <details><summary><b><a href="https://github.com/JohnSnowLabs/spark-nlp">spark-nlp</a></b> (πŸ₯ˆ35 Β· ⭐ 4.1K) - State of the Art Natural Language Processing. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 730 Β· πŸ“¦ 620 Β· πŸ“‹ 910 - 2% open Β· ⏱️ 22.10.2025):

    git clone https://github.com/JohnSnowLabs/spark-nlp
    
  • PyPi (πŸ“₯ 1M / month Β· πŸ“¦ 39 Β· ⏱️ 22.10.2025):

    pip install spark-nlp
    
</details> <details><summary><b><a href="https://github.com/RasaHQ/rasa">Rasa</a></b> (πŸ₯ˆ34 Β· ⭐ 21K) - Open source machine learning framework to automate text- and voice-.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 600 Β· πŸ”€ 4.9K Β· πŸ“‹ 6.8K - 2% open Β· ⏱️ 26.08.2025):

    git clone https://github.com/RasaHQ/rasa
    
  • PyPi (πŸ“₯ 110K / month Β· πŸ“¦ 60 Β· ⏱️ 14.01.2025):

    pip install rasa
    
</details> <details><summary><b><a href="https://github.com/tensorflow/text">TensorFlow Text</a></b> (πŸ₯ˆ34 Β· ⭐ 1.3K) - Making text a first-class citizen in TensorFlow. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 360 Β· πŸ“¦ 10K Β· πŸ“‹ 370 - 53% open Β· ⏱️ 18.08.2025):

    git clone https://github.com/tensorflow/text
    
  • PyPi (πŸ“₯ 6.8M / month Β· πŸ“¦ 230 Β· ⏱️ 04.04.2025):

    pip install tensorflow-text
    
</details> <details><summary><b><a href="https://github.com/snowballstem/snowball">snowballstemmer</a></b> (πŸ₯ˆ34 Β· ⭐ 810) - Snowball compiler and stemming algorithms. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 190 Β· πŸ“¦ 11 Β· πŸ“‹ 120 - 17% open Β· ⏱️ 28.10.2025):

    git clone https://github.com/snowballstem/snowball
    
  • PyPi (πŸ“₯ 24M / month Β· πŸ“¦ 550 Β· ⏱️ 09.05.2025):

    pip install snowballstemmer
    
  • Conda (πŸ“₯ 11M Β· ⏱️ 20.05.2025):

    conda install -c conda-forge snowballstemmer
    
</details> <details><summary><b><a href="https://github.com/pytorch/text">torchtext</a></b> (πŸ₯ˆ32 Β· ⭐ 3.6K) - Models, data loaders and abstractions for language processing,.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 810 Β· πŸ“‹ 850 - 38% open Β· ⏱️ 10.09.2025):

    git clone https://github.com/pytorch/text
    
  • PyPi (πŸ“₯ 730K / month Β· πŸ“¦ 280 Β· ⏱️ 24.04.2024):

    pip install torchtext
    
</details> <details><summary><b><a href="https://github.com/jamesturk/jellyfish">jellyfish</a></b> (πŸ₯ˆ32 Β· ⭐ 2.2K) - a python library for doing approximate and phonetic matching of strings. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 37 Β· πŸ”€ 160 Β· πŸ“¦ 15K Β· ⏱️ 11.10.2025):

    git clone https://github.com/jamesturk/jellyfish
    
  • PyPi (πŸ“₯ 8.6M / month Β· πŸ“¦ 320 Β· ⏱️ 11.10.2025):

    pip install jellyfish
    
  • Conda (πŸ“₯ 1.7M Β· ⏱️ 22.04.2025):

    conda install -c conda-forge jellyfish
    
</details> <details><summary><b><a href="https://github.com/deeppavlov/DeepPavlov">DeepPavlov</a></b> (πŸ₯ˆ31 Β· ⭐ 6.9K Β· πŸ’€) - An open source library for deep learning end-to-end.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 78 Β· πŸ”€ 1.2K Β· πŸ“¦ 440 Β· πŸ“‹ 640 - 4% open Β· ⏱️ 26.11.2024):

    git clone https://github.com/deepmipt/DeepPavlov
    
  • PyPi (πŸ“₯ 11K / month Β· πŸ“¦ 4 Β· ⏱️ 12.08.2024):

    pip install deeppavlov
    
</details> <details><summary><b><a href="https://github.com/rspeer/python-ftfy">ftfy</a></b> (πŸ₯ˆ31 Β· ⭐ 4K Β· πŸ’€) - Fixes mojibake and other glitches in Unicode text, after the fact. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 120 Β· πŸ“₯ 100 Β· πŸ“¦ 33K Β· πŸ“‹ 150 - 7% open Β· ⏱️ 30.10.2024):

    git clone https://github.com/rspeer/python-ftfy
    
  • PyPi (πŸ“₯ 11M / month Β· πŸ“¦ 570 Β· ⏱️ 26.10.2024):

    pip install ftfy
    
  • Conda (πŸ“₯ 380K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge ftfy
    
</details> <details><summary><b><a href="https://github.com/allenai/scispacy">SciSpacy</a></b> (πŸ₯ˆ31 Β· ⭐ 1.9K) - A full spaCy pipeline and models for scientific/biomedical documents. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 240 Β· πŸ“¦ 1.3K Β· πŸ“‹ 330 - 11% open Β· ⏱️ 01.10.2025):

    git clone https://github.com/allenai/scispacy
    
  • PyPi (πŸ“₯ 42K / month Β· πŸ“¦ 50 Β· ⏱️ 01.10.2025):

    pip install scispacy
    
</details> <details><summary><b><a href="https://github.com/cltk/cltk">CLTK</a></b> (πŸ₯ˆ31 Β· ⭐ 870 Β· πŸ“‰) - The Classical Language Toolkit. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 340 Β· πŸ“₯ 160 Β· πŸ“¦ 300 Β· πŸ“‹ 580 - 0% open Β· ⏱️ 21.10.2025):

    git clone https://github.com/cltk/cltk
    
  • PyPi (πŸ“₯ 14K / month Β· πŸ“¦ 17 Β· ⏱️ 21.10.2025):

    pip install cltk
    
</details> <details><summary><b><a href="https://github.com/dwyl/english-words">english-words</a></b> (πŸ₯ˆ29 Β· ⭐ 12K Β· πŸ’€) - A text file containing 479k English words for all your.. <code><a href="http://bit.ly/3rvuUlR">Unlicense</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 2K Β· πŸ“¦ 2 Β· πŸ“‹ 170 - 75% open Β· ⏱️ 06.01.2025):

    git clone https://github.com/dwyl/english-words
    
  • PyPi (πŸ“₯ 78K / month Β· πŸ“¦ 15 Β· ⏱️ 14.08.2025):

    pip install english-words
    
</details> <details><summary><b><a href="https://github.com/argilla-io/argilla">rubrix</a></b> (πŸ₯ˆ29 Β· ⭐ 4.7K) - Argilla is a collaboration tool for AI engineers and domain experts.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 460 Β· πŸ“¦ 3.1K Β· πŸ“‹ 2.2K - 0% open Β· ⏱️ 05.08.2025):

    git clone https://github.com/recognai/rubrix
    
  • PyPi (πŸ“₯ 1.2K / month Β· ⏱️ 24.10.2022):

    pip install rubrix
    
  • Conda (πŸ“₯ 52K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge rubrix
    
</details> <details><summary><b><a href="https://github.com/dedupeio/dedupe">Dedupe</a></b> (πŸ₯ˆ29 Β· ⭐ 4.4K Β· πŸ“ˆ) - A python library for accurate and scalable fuzzy matching, record.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 72 Β· πŸ”€ 560 Β· πŸ“¦ 370 Β· πŸ“‹ 820 - 9% open Β· ⏱️ 29.07.2025):

    git clone https://github.com/dedupeio/dedupe
    
  • PyPi (πŸ“₯ 59K / month Β· πŸ“¦ 19 Β· ⏱️ 15.08.2024):

    pip install dedupe
    
  • Conda (πŸ“₯ 130K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge dedupe
    
</details> <details><summary><b><a href="https://github.com/life4/textdistance">TextDistance</a></b> (πŸ₯ˆ28 Β· ⭐ 3.5K) - Compute distance between sequences. 30+ algorithms, pure python.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 260 Β· πŸ“₯ 1.1K Β· πŸ“¦ 8.8K Β· ⏱️ 18.04.2025):

    git clone https://github.com/life4/textdistance
    
  • PyPi (πŸ“₯ 1.3M / month Β· πŸ“¦ 99 Β· ⏱️ 16.07.2024):

    pip install textdistance
    
  • Conda (πŸ“₯ 970K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge textdistance
    
</details> <details><summary><b><a href="https://github.com/explosion/spacy-transformers">spacy-transformers</a></b> (πŸ₯ˆ28 Β· ⭐ 1.4K) - Use pretrained transformers like BERT, XLNet and GPT-2.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code>spacy</code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 170 Β· πŸ“₯ 610 Β· πŸ“¦ 2.4K Β· ⏱️ 26.05.2025):

    git clone https://github.com/explosion/spacy-transformers
    
  • PyPi (πŸ“₯ 270K / month Β· πŸ“¦ 110 Β· ⏱️ 26.05.2025):

    pip install spacy-transformers
    
  • Conda (πŸ“₯ 140K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge spacy-transformers
    
</details> <details><summary><b><a href="https://github.com/unitaryai/detoxify">detoxify</a></b> (πŸ₯‰26 Β· ⭐ 1.1K) - Trained models & code to predict toxic comments on all 3 Jigsaw.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 130 Β· πŸ“₯ 1.9M Β· πŸ“¦ 980 Β· πŸ“‹ 67 - 55% open Β· ⏱️ 29.07.2025):

    git clone https://github.com/unitaryai/detoxify
    
  • PyPi (πŸ“₯ 140K / month Β· πŸ“¦ 30 Β· ⏱️ 01.02.2024):

    pip install detoxify
    
</details> <details><summary><b><a href="https://github.com/JasonKessler/scattertext">scattertext</a></b> (πŸ₯‰25 Β· ⭐ 2.3K) - Beautiful visualizations of how language differs among document.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 290 Β· πŸ“¦ 670 Β· πŸ“‹ 100 - 22% open Β· ⏱️ 29.04.2025):

    git clone https://github.com/JasonKessler/scattertext
    
  • PyPi (πŸ“₯ 7.5K / month Β· πŸ“¦ 5 Β· ⏱️ 23.09.2024):

    pip install scattertext
    
  • Conda (πŸ“₯ 140K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge scattertext
    
</details> <details><summary><b><a href="https://github.com/google-research/text-to-text-transfer-transformer">T5</a></b> (πŸ₯‰24 Β· ⭐ 6.4K) - Code for the paper Exploring the Limits of Transfer Learning with a.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 780 Β· πŸ“‹ 450 - 23% open Β· ⏱️ 28.04.2025):

    git clone https://github.com/google-research/text-to-text-transfer-transformer
    
  • PyPi (πŸ“₯ 83K / month Β· πŸ“¦ 2 Β· ⏱️ 18.10.2021):

    pip install t5
    
</details> <details><summary><b><a href="https://github.com/zjunlp/DeepKE">DeepKE</a></b> (πŸ₯‰24 Β· ⭐ 4.2K) - [EMNLP 2022] An Open Toolkit for Knowledge Graph Extraction and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 730 Β· πŸ“¦ 25 Β· ⏱️ 19.07.2025):

    git clone https://github.com/zjunlp/deepke
    
  • PyPi (πŸ“₯ 950 / month Β· ⏱️ 21.09.2023):

    pip install deepke
    
</details> <details><summary><b><a href="https://github.com/explosion/sense2vec">sense2vec</a></b> (πŸ₯‰24 Β· ⭐ 1.7K) - Contextually-keyed word vectors. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 20 Β· πŸ”€ 240 Β· πŸ“₯ 73K Β· πŸ“¦ 470 Β· πŸ“‹ 120 - 20% open Β· ⏱️ 23.04.2025):

    git clone https://github.com/explosion/sense2vec
    
  • PyPi (πŸ“₯ 3.4K / month Β· πŸ“¦ 13 Β· ⏱️ 19.04.2021):

    pip install sense2vec
    
  • Conda (πŸ“₯ 67K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge sense2vec
    
</details> <details><summary><b><a href="https://github.com/IndicoDataSolutions/finetune">finetune</a></b> (πŸ₯‰23 Β· ⭐ 720) - Scikit-learn style model finetuning for NLP. <code><a href="http://bit.ly/3postzC">MPL-2.0</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 79 Β· πŸ“¦ 16 Β· πŸ“‹ 190 - 39% open Β· ⏱️ 21.10.2025):

    git clone https://github.com/IndicoDataSolutions/finetune
    
  • PyPi (πŸ“₯ 2.7K / month Β· πŸ“¦ 2 Β· ⏱️ 29.09.2023):

    pip install finetune
    
</details> <details><summary><b><a href="https://github.com/EricFillion/happy-transformer">happy-transformer</a></b> (πŸ₯‰23 Β· ⭐ 540 Β· πŸ’€) - Happy Transformer makes it easy to fine-tune and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code>huggingface</code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 69 Β· πŸ“¦ 330 Β· πŸ“‹ 130 - 16% open Β· ⏱️ 22.03.2025):

    git clone https://github.com/EricFillion/happy-transformer
    
  • PyPi (πŸ“₯ 2.7K / month Β· πŸ“¦ 5 Β· ⏱️ 05.08.2023):

    pip install happytransformer
    
</details> <details><summary><b><a href="https://github.com/awslabs/sockeye">Sockeye</a></b> (πŸ₯‰21 Β· ⭐ 1.2K Β· πŸ’€) - Sequence-to-sequence framework with a focus on Neural.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1X" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 60 Β· πŸ”€ 320 Β· πŸ“₯ 21 Β· πŸ“‹ 310 - 3% open Β· ⏱️ 24.10.2024):

    git clone https://github.com/awslabs/sockeye
    
  • PyPi (πŸ“₯ 580 / month Β· ⏱️ 03.03.2023):

    pip install sockeye
    
</details> <details><summary><b><a href="https://github.com/unum-cloud/UForm">UForm</a></b> (πŸ₯‰21 Β· ⭐ 1.2K) - Pocket-Sized Multimodal AI for content understanding and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 76 Β· πŸ“₯ 710 Β· πŸ“¦ 36 Β· πŸ“‹ 39 - 38% open Β· ⏱️ 03.09.2025):

    git clone https://github.com/unum-cloud/uform
    
  • PyPi (πŸ“₯ 490 / month Β· πŸ“¦ 2 Β· ⏱️ 03.09.2025):

    pip install uform
    
</details> <details><summary><b><a href="https://github.com/webis-de/small-text">small-text</a></b> (πŸ₯‰20 Β· ⭐ 630) - Active Learning for Text Classification in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 76 Β· πŸ“¦ 34 Β· πŸ“‹ 74 - 28% open Β· ⏱️ 28.10.2025):

    git clone https://github.com/webis-de/small-text
    
  • PyPi (πŸ“₯ 390 / month Β· ⏱️ 17.08.2025):

    pip install small-text
    
  • Conda (πŸ“₯ 19K Β· ⏱️ 17.08.2025):

    conda install -c conda-forge small-text
    
</details> <details><summary><b><a href="https://github.com/dsfsi/textaugment">textaugment</a></b> (πŸ₯‰19 Β· ⭐ 430) - TextAugment: Text Augmentation Library. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 60 Β· πŸ“₯ 140 Β· πŸ“¦ 180 Β· πŸ“‹ 29 - 37% open Β· ⏱️ 09.09.2025):

    git clone https://github.com/dsfsi/textaugment
    
  • PyPi (πŸ“₯ 4.2K / month Β· πŸ“¦ 4 Β· ⏱️ 16.11.2023):

    pip install textaugment
    
</details> <details><summary><b><a href="https://github.com/facebookresearch/vizseq">VizSeq</a></b> (πŸ₯‰15 Β· ⭐ 450) - An Analysis Toolkit for Natural Language Generation (Translation,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 4 Β· πŸ”€ 61 Β· πŸ“¦ 13 Β· πŸ“‹ 16 - 43% open Β· ⏱️ 24.06.2025):

    git clone https://github.com/facebookresearch/vizseq
    
  • PyPi (πŸ“₯ 120 / month Β· ⏱️ 07.08.2020):

    pip install vizseq
    
</details> <details><summary>Show 59 hidden projects...</summary>
  • <b><a href="https://github.com/allenai/allennlp">AllenNLP</a></b> (πŸ₯ˆ36 Β· ⭐ 12K Β· πŸ’€) - An open-source NLP research library, built on PyTorch. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/facebookresearch/fastText">fastText</a></b> (πŸ₯ˆ34 Β· ⭐ 26K Β· πŸ’€) - Library for fast text representation and classification. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/OpenNMT/OpenNMT-py">OpenNMT</a></b> (πŸ₯ˆ33 Β· ⭐ 7K Β· πŸ’€) - Open Source Neural Machine Translation and (Large) Language Models.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/facebookresearch/ParlAI">ParlAI</a></b> (πŸ₯ˆ32 Β· ⭐ 11K Β· πŸ’€) - A framework for training and evaluating AI models on a variety of.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/seatgeek/fuzzywuzzy">fuzzywuzzy</a></b> (πŸ₯ˆ31 Β· ⭐ 9.3K Β· πŸ’€) - Fuzzy String Matching in Python. <code><a href="http://bit.ly/2KucAZR">❗️GPL-2.0</a></code>
  • <b><a href="https://github.com/miso-belica/sumy">Sumy</a></b> (πŸ₯ˆ30 Β· ⭐ 3.6K Β· πŸ’€) - Module for automatic summarization of text documents and HTML pages. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/undertheseanlp/underthesea">underthesea</a></b> (πŸ₯ˆ30 Β· ⭐ 1.6K) - Underthesea - Vietnamese NLP Toolkit. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code>
  • <b><a href="https://github.com/makcedward/nlpaug">nlpaug</a></b> (πŸ₯ˆ29 Β· ⭐ 4.6K Β· πŸ’€) - Data augmentation for NLP. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/cjhutto/vaderSentiment">vaderSentiment</a></b> (πŸ₯ˆ28 Β· ⭐ 4.9K Β· πŸ’€) - VADER Sentiment Analysis. VADER (Valence Aware Dictionary.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/chartbeat-labs/textacy">textacy</a></b> (πŸ₯ˆ28 Β· ⭐ 2.2K Β· πŸ’€) - NLP, before and after spaCy. <code>❗Unlicensed</code>
  • <b><a href="https://github.com/DerwenAI/pytextrank">PyTextRank</a></b> (πŸ₯ˆ28 Β· ⭐ 2.2K Β· πŸ’€) - Python implementation of TextRank algorithms (textgraphs) for.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/bee-san/Ciphey">Ciphey</a></b> (πŸ₯‰27 Β· ⭐ 20K Β· πŸ’€) - Automatically decrypt encryptions without knowing the key or cipher,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/fastnlp/fastNLP">fastNLP</a></b> (πŸ₯‰27 Β· ⭐ 3.1K Β· πŸ’€) - fastNLP: A Modularized and Extensible NLP Framework. Currently.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/aboSamoor/polyglot">polyglot</a></b> (πŸ₯‰27 Β· ⭐ 2.3K Β· πŸ’€) - Multilingual text (NLP) processing toolkit. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code>
  • <b><a href="https://github.com/vi3k6i5/flashtext">flashtext</a></b> (πŸ₯‰26 Β· ⭐ 5.7K Β· πŸ’€) - Extract Keywords from sentence or Replace keywords in sentences. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/saffsd/langid.py">langid</a></b> (πŸ₯‰26 Β· ⭐ 2.4K Β· πŸ’€) - Stand-alone language identification system. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/nipunsadvilkar/pySBD">pySBD</a></b> (πŸ₯‰26 Β· ⭐ 880 Β· πŸ’€) - pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/huggingface/neuralcoref">neuralcoref</a></b> (πŸ₯‰25 Β· ⭐ 2.9K Β· πŸ’€) - Fast Coreference Resolution in spaCy with Neural Networks. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/dmlc/gluon-nlp">GluonNLP</a></b> (πŸ₯‰25 Β· ⭐ 2.6K Β· πŸ’€) - Toolkit that enables easy text preprocessing, datasets.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1X" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/PetrochukM/PyTorch-NLP">pytorch-nlp</a></b> (πŸ₯‰25 Β· ⭐ 2.2K Β· πŸ’€) - Basic Utilities for PyTorch Natural Language Processing.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/mchaput/whoosh">whoosh</a></b> (πŸ₯‰25 Β· ⭐ 640 Β· πŸ’€) - Pure-Python full-text search library. <code><a href="https://tldrlegal.com/search?q=BSD-1-Clause">❗️BSD-1-Clause</a></code>
  • <b><a href="https://github.com/facebookresearch/pytext">PyText</a></b> (πŸ₯‰24 Β· ⭐ 6.3K Β· πŸ’€) - A natural language modeling framework based on PyTorch. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/minimaxir/textgenrnn">textgenrnn</a></b> (πŸ₯‰24 Β· ⭐ 4.9K Β· πŸ’€) - Easily train your own text-generating neural network of any.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/thunlp/OpenPrompt">OpenPrompt</a></b> (πŸ₯‰24 Β· ⭐ 4.7K Β· πŸ’€) - An Open-Source Framework for Prompt-Learning. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/snipsco/snips-nlu">Snips NLU</a></b> (πŸ₯‰24 Β· ⭐ 3.9K Β· πŸ’€) - Snips Python library to extract meaning from text. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/NTMC-Community/MatchZoo">MatchZoo</a></b> (πŸ₯‰24 Β· ⭐ 3.9K Β· πŸ’€) - Facilitating the design, comparison and sharing of deep.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/bigscience-workshop/promptsource">promptsource</a></b> (πŸ₯‰24 Β· ⭐ 3K Β· πŸ’€) - Toolkit for creating, sharing and using natural language.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/VKCOM/YouTokenToMe">YouTokenToMe</a></b> (πŸ₯‰24 Β· ⭐ 970 Β· πŸ’€) - Unsupervised text tokenizer focused on computational efficiency. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/BrikerMan/Kashgari">Kashgari</a></b> (πŸ₯‰23 Β· ⭐ 2.4K Β· πŸ’€) - Kashgari is a production-level NLP Transfer learning.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/deepset-ai/FARM">FARM</a></b> (πŸ₯‰23 Β· ⭐ 1.8K Β· πŸ’€) - Fast & easy transfer learning for NLP. Harvesting language.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/minimaxir/gpt-2-simple">gpt-2-simple</a></b> (πŸ₯‰22 Β· ⭐ 3.4K Β· πŸ’€) - Python package to easily retrain OpenAIs GPT-2 text-.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/asyml/texar">Texar</a></b> (πŸ₯‰22 Β· ⭐ 2.4K Β· πŸ’€) - Toolkit for Machine Learning, Natural Language Processing, and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/nyu-mll/jiant">jiant</a></b> (πŸ₯‰22 Β· ⭐ 1.7K Β· πŸ’€) - jiant is an nlp toolkit. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/Alir3z4/python-stop-words">stop-words</a></b> (πŸ₯‰22 Β· ⭐ 160) - Get list of common stop words in various languages in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/IntelLabs/nlp-architect">NLP Architect</a></b> (πŸ₯‰21 Β· ⭐ 2.9K Β· πŸ’€) - A model library for exploring state-of-the-art deep.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/jbesomi/texthero">Texthero</a></b> (πŸ₯‰21 Β· ⭐ 2.9K Β· πŸ’€) - Text preprocessing, representation and visualization from zero to.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/Hironsan/anago">anaGo</a></b> (πŸ₯‰21 Β· ⭐ 1.5K Β· πŸ’€) - Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/bytedance/lightseq">lightseq</a></b> (πŸ₯‰20 Β· ⭐ 3.3K Β· πŸ’€) - LightSeq: A High Performance Library for Sequence Processing.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/appvision-ai/fast-bert">fast-bert</a></b> (πŸ₯‰20 Β· ⭐ 1.9K Β· πŸ’€) - Super easy library for BERT based NLP models. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/Delta-ML/delta">DELTA</a></b> (πŸ₯‰20 Β· ⭐ 1.6K Β· πŸ’€) - DELTA is a deep learning based natural language and speech.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/textpipe/textpipe">textpipe</a></b> (πŸ₯‰20 Β· ⭐ 300 Β· πŸ’€) - Textpipe: clean and extract metadata from text. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/jaidevd/numerizer">numerizer</a></b> (πŸ₯‰19 Β· ⭐ 230 Β· πŸ’€) - A Python module to convert natural language numerics into ints and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/vrasneur/pyfasttext">pyfasttext</a></b> (πŸ₯‰19 Β· ⭐ 230 Β· πŸ’€) - Yet another Python binding for fastText. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code>
  • <b><a href="https://github.com/anhaidgroup/deepmatcher">DeepMatcher</a></b> (πŸ₯‰18 Β· ⭐ 5.2K Β· πŸ’€) - Python package for performing Entity and Text Matching using.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/koursaros-ai/nboost">nboost</a></b> (πŸ₯‰18 Β· ⭐ 670 Β· πŸ’€) - NBoost is a scalable, search-api-boosting platform for deploying.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/Ki6an/fastT5">fastT5</a></b> (πŸ₯‰18 Β· ⭐ 590 Β· πŸ’€) - boost inference speed of T5 models by 5x & reduce the model size.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/PKSHATechnology-Research/camphr">Camphr</a></b> (πŸ₯‰18 Β· ⭐ 340 Β· πŸ’€) - Camphr - NLP libary for creating pipeline components. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code>spacy</code>
  • <b><a href="https://github.com/Franck-Dernoncourt/NeuroNER">NeuroNER</a></b> (πŸ₯‰17 Β· ⭐ 1.7K Β· πŸ’€) - Named-entity recognition using neural networks. Easy-to-use and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/thunlp/OpenNRE">OpenNRE</a></b> (πŸ₯‰16 Β· ⭐ 4.4K Β· πŸ’€) - An Open-Source Package for Neural Relation Extraction (NRE). <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/facebookresearch/BLINK">BLINK</a></b> (πŸ₯‰15 Β· ⭐ 1.2K Β· πŸ’€) - Entity Linker solution. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/RUCAIBox/TextBox">TextBox</a></b> (πŸ₯‰15 Β· ⭐ 1.1K Β· πŸ’€) - TextBox 2.0 is a text generation library with pre-trained language.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/pytorch/translate">Translate</a></b> (πŸ₯‰15 Β· ⭐ 830 Β· πŸ’€) - Translate - a PyTorch Language Library. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/shaypal5/skift">skift</a></b> (πŸ₯‰15 Β· ⭐ 240 Β· πŸ’€) - scikit-learn wrappers for Python fastText. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/abelriboulot/onnxt5">ONNX-T5</a></b> (πŸ₯‰14 Β· ⭐ 260 Β· πŸ’€) - Summarization, translation, sentiment-analysis, text-generation.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/victordibia/neuralqa">NeuralQA</a></b> (πŸ₯‰14 Β· ⭐ 230 Β· πŸ’€) - NeuralQA: A Usable Library for Question Answering on Large Datasets.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/feedly/transfer-nlp">TransferNLP</a></b> (πŸ₯‰13 Β· ⭐ 290 Β· πŸ’€) - NLP library designed for reproducible experimentation.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/spring-media/headliner">Headliner</a></b> (πŸ₯‰13 Β· ⭐ 230 Β· πŸ’€) - Easy training and deployment of seq2seq models. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/textvec/textvec">textvec</a></b> (πŸ₯‰12 Β· ⭐ 200 Β· πŸ’€) - Text vectorization tool to outperform TFIDF for classification.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/MartinoMensio/spacy-dbpedia-spotlight">spacy-dbpedia-spotlight</a></b> (πŸ₯‰12 Β· ⭐ 110 Β· πŸ’€) - A spaCy wrapper for DBpedia Spotlight. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code>spacy</code>
</details> <br>

Image Data

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries for image & video processing, manipulation, and augmentation as well as libraries for computer vision tasks such as facial recognition, object detection, and classification.

<details><summary><b><a href="https://github.com/python-pillow/Pillow">Pillow</a></b> (πŸ₯‡49 Β· ⭐ 13K) - Python Imaging Library (Fork). <code><a href="https://tldrlegal.com/search?q=PIL">❗️PIL</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 490 Β· πŸ”€ 2.3K Β· πŸ“¦ 2.4M Β· πŸ“‹ 3.4K - 3% open Β· ⏱️ 27.10.2025):

    git clone https://github.com/python-pillow/Pillow
    
  • PyPi (πŸ“₯ 220M / month Β· πŸ“¦ 20K Β· ⏱️ 15.10.2025):

    pip install Pillow
    
  • Conda (πŸ“₯ 62M Β· ⏱️ 28.10.2025):

    conda install -c conda-forge pillow
    
</details> <details><summary><b><a href="https://github.com/huggingface/pytorch-image-models">PyTorch Image Models</a></b> (πŸ₯‡42 Β· ⭐ 36K) - The largest collection of PyTorch image encoders /.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 5.1K Β· πŸ“₯ 8.4M Β· πŸ“¦ 62K Β· πŸ“‹ 1K - 4% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/rwightman/pytorch-image-models
    
  • PyPi (πŸ“₯ 11M / month Β· πŸ“¦ 1.5K Β· ⏱️ 24.10.2025):

    pip install timm
    
  • Conda (πŸ“₯ 470K Β· ⏱️ 24.10.2025):

    conda install -c conda-forge timm
    
</details> <details><summary><b><a href="https://github.com/pytorch/vision">torchvision</a></b> (πŸ₯‡42 Β· ⭐ 17K) - Datasets, Transforms and Models specific to Computer Vision. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 660 Β· πŸ”€ 7.2K Β· πŸ“₯ 41K Β· πŸ“¦ 21 Β· πŸ“‹ 3.8K - 30% open Β· ⏱️ 27.10.2025):

    git clone https://github.com/pytorch/vision
    
  • PyPi (πŸ“₯ 26M / month Β· πŸ“¦ 8.4K Β· ⏱️ 15.10.2025):

    pip install torchvision
    
  • Conda (πŸ“₯ 3.1M Β· ⏱️ 23.10.2025):

    conda install -c conda-forge torchvision
    
</details> <details><summary><b><a href="https://github.com/Zulko/moviepy">MoviePy</a></b> (πŸ₯‡42 Β· ⭐ 14K) - Video editing with Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 1.9K Β· πŸ“¦ 67K Β· πŸ“‹ 1.7K - 3% open Β· ⏱️ 25.09.2025):

    git clone https://github.com/Zulko/moviepy
    
  • PyPi (πŸ“₯ 4.3M / month Β· πŸ“¦ 1.2K Β· ⏱️ 21.05.2025):

    pip install moviepy
    
  • Conda (πŸ“₯ 360K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge moviepy
    
</details> <details><summary><b><a href="https://github.com/kornia/kornia">Kornia</a></b> (πŸ₯‡39 Β· ⭐ 11K) - Geometric Computer Vision Library for Spatial AI. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 300 Β· πŸ”€ 1.1K Β· πŸ“₯ 2.2K Β· πŸ“¦ 17K Β· πŸ“‹ 1K - 32% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/kornia/kornia
    
  • PyPi (πŸ“₯ 3M / month Β· πŸ“¦ 340 Β· ⏱️ 08.05.2025):

    pip install kornia
    
  • Conda (πŸ“₯ 260K Β· ⏱️ 08.05.2025):

    conda install -c conda-forge kornia
    
</details> <details><summary><b><a href="https://github.com/imageio/imageio">imageio</a></b> (πŸ₯‡39 Β· ⭐ 1.7K) - Python library for reading and writing image data. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 330 Β· πŸ“₯ 1.9K Β· πŸ“¦ 180K Β· πŸ“‹ 620 - 16% open Β· ⏱️ 24.10.2025):

    git clone https://github.com/imageio/imageio
    
  • PyPi (πŸ“₯ 36M / month Β· πŸ“¦ 2.6K Β· ⏱️ 20.01.2025):

    pip install imageio
    
  • Conda (πŸ“₯ 8.5M Β· ⏱️ 22.04.2025):

    conda install -c conda-forge imageio
    
</details> <details><summary><b><a href="https://github.com/serengil/deepface">deepface</a></b> (πŸ₯ˆ38 Β· ⭐ 21K Β· πŸ“‰) - A Lightweight Face Recognition and Facial Attribute Analysis (Age,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 96 Β· πŸ”€ 2.8K Β· πŸ“¦ 8.4K Β· πŸ“‹ 1.2K - 0% open Β· ⏱️ 21.10.2025):

    git clone https://github.com/serengil/deepface
    
  • PyPi (πŸ“₯ 280K / month Β· πŸ“¦ 78 Β· ⏱️ 05.08.2025):

    pip install deepface
    
</details> <details><summary><b><a href="https://github.com/deepinsight/insightface">InsightFace</a></b> (πŸ₯ˆ37 Β· ⭐ 27K) - State-of-the-art 2D and 3D Face Analysis Project. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1X" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 67 Β· πŸ”€ 5.7K Β· πŸ“₯ 11M Β· πŸ“¦ 4.8K Β· πŸ“‹ 2.6K - 46% open Β· ⏱️ 27.09.2025):

    git clone https://github.com/deepinsight/insightface
    
  • PyPi (πŸ“₯ 350K / month Β· πŸ“¦ 30 Β· ⏱️ 17.12.2022):

    pip install insightface
    
</details> <details><summary><b><a href="https://github.com/albumentations-team/albumentations">Albumentations</a></b> (πŸ₯ˆ36 Β· ⭐ 15K) - Fast and flexible image augmentation library. Paper about.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 1.7K Β· πŸ“‹ 1.5K - 14% open Β· ⏱️ 25.06.2025):

    git clone https://github.com/albumentations-team/albumentations
    
  • PyPi (πŸ“₯ 4.6M / month Β· πŸ“¦ 730 Β· ⏱️ 27.05.2025):

    pip install albumentations
    
  • Conda (πŸ“₯ 340K Β· ⏱️ 28.05.2025):

    conda install -c conda-forge albumentations
    
</details> <details><summary><b><a href="https://github.com/opencv/opencv-python">opencv-python</a></b> (πŸ₯ˆ36 Β· ⭐ 5.1K) - Automated CI toolchain to produce precompiled opencv-python,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 950 Β· πŸ“¦ 610K Β· πŸ“‹ 890 - 19% open Β· ⏱️ 30.07.2025):

    git clone https://github.com/opencv/opencv-python
    
  • PyPi (πŸ“₯ 29M / month Β· πŸ“¦ 15K Β· ⏱️ 07.07.2025):

    pip install opencv-python
    
</details> <details><summary><b><a href="https://github.com/facebookresearch/detectron2">detectron2</a></b> (πŸ₯ˆ34 Β· ⭐ 34K) - Detectron2 is a platform for object detection, segmentation.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 280 Β· πŸ”€ 7.5K Β· πŸ“¦ 2.6K Β· πŸ“‹ 3.6K - 14% open Β· ⏱️ 27.10.2025):

    git clone https://github.com/facebookresearch/detectron2
    
  • PyPi (πŸ“¦ 13 Β· ⏱️ 06.02.2020):

    pip install detectron2
    
  • Conda (πŸ“₯ 820K Β· ⏱️ 02.06.2025):

    conda install -c conda-forge detectron2
    
</details> <details><summary><b><a href="https://github.com/emcconville/wand">Wand</a></b> (πŸ₯ˆ34 Β· ⭐ 1.5K) - The ctypes-based simple ImageMagick binding for Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 200 Β· πŸ“₯ 52K Β· πŸ“¦ 21K Β· πŸ“‹ 440 - 5% open Β· ⏱️ 06.10.2025):

    git clone https://github.com/emcconville/wand
    
  • PyPi (πŸ“₯ 2.2M / month Β· πŸ“¦ 260 Β· ⏱️ 03.11.2023):

    pip install wand
    
  • Conda (πŸ“₯ 180K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge wand
    
</details> <details><summary><b><a href="https://github.com/JohannesBuchner/imagehash">ImageHash</a></b> (πŸ₯ˆ32 Β· ⭐ 3.7K) - A Python Perceptual Image Hashing Module. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 340 Β· πŸ“¦ 18K Β· πŸ“‹ 150 - 15% open Β· ⏱️ 17.04.2025):

    git clone https://github.com/JohannesBuchner/imagehash
    
  • PyPi (πŸ“₯ 5.6M / month Β· πŸ“¦ 270 Β· ⏱️ 01.02.2025):

    pip install ImageHash
    
  • Conda (πŸ“₯ 500K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge imagehash
    
</details> <details><summary><b><a href="https://github.com/lucidrains/vit-pytorch">vit-pytorch</a></b> (πŸ₯ˆ31 Β· ⭐ 24K) - Implementation of Vision Transformer, a simple way to achieve.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 3.4K Β· πŸ“¦ 21 Β· πŸ“‹ 290 - 49% open Β· ⏱️ 28.10.2025):

    git clone https://github.com/lucidrains/vit-pytorch
    
  • PyPi (πŸ“₯ 31K / month Β· πŸ“¦ 28 Β· ⏱️ 27.10.2025):

    pip install vit-pytorch
    
</details> <details><summary><b><a href="https://github.com/PaddlePaddle/PaddleSeg">PaddleSeg</a></b> (πŸ₯ˆ31 Β· ⭐ 9.2K) - Easy-to-use image segmentation library with awesome pre-.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1M" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 1.7K Β· πŸ“¦ 1.5K Β· πŸ“‹ 2.2K - 0% open Β· ⏱️ 10.10.2025):

    git clone https://github.com/PaddlePaddle/PaddleSeg
    
  • PyPi (πŸ“₯ 3.8K / month Β· πŸ“¦ 7 Β· ⏱️ 30.11.2022):

    pip install paddleseg
    
</details> <details><summary><b><a href="https://github.com/obss/sahi">sahi</a></b> (πŸ₯ˆ31 Β· ⭐ 4.9K) - Framework agnostic sliced/tiled inference + interactive ui + error analysis.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 69 Β· πŸ”€ 700 Β· πŸ“₯ 43K Β· πŸ“¦ 1.9K Β· ⏱️ 28.10.2025):

    git clone https://github.com/obss/sahi
    
  • PyPi (πŸ“₯ 140K / month Β· πŸ“¦ 43 Β· ⏱️ 28.09.2025):

    pip install sahi
    
  • Conda (πŸ“₯ 120K Β· ⏱️ 29.09.2025):

    conda install -c conda-forge sahi
    
</details> <details><summary><b><a href="https://github.com/lightly-ai/lightly">lightly</a></b> (πŸ₯ˆ31 Β· ⭐ 3.6K) - A python library for self-supervised learning on images. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 72 Β· πŸ”€ 310 Β· πŸ“¦ 510 Β· πŸ“‹ 610 - 12% open Β· ⏱️ 25.09.2025):

    git clone https://github.com/lightly-ai/lightly
    
  • PyPi (πŸ“₯ 190K / month Β· πŸ“¦ 20 Β· ⏱️ 22.07.2025):

    pip install lightly
    
</details> <details><summary><b><a href="https://github.com/mindee/doctr">doctr</a></b> (πŸ₯ˆ29 Β· ⭐ 5.6K) - docTR (Document Text Recognition) - a seamless, high-.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 68 Β· πŸ”€ 580 Β· πŸ“₯ 6.5M Β· πŸ“‹ 440 - 6% open Β· ⏱️ 07.09.2025):

    git clone https://github.com/mindee/doctr
    
  • PyPi (πŸ“₯ 2M / month Β· πŸ“¦ 18 Β· ⏱️ 09.07.2025):

    pip install python-doctr
    
</details> <details><summary><b><a href="https://github.com/PaddlePaddle/PaddleDetection">PaddleDetection</a></b> (πŸ₯‰28 Β· ⭐ 14K) - Object Detection toolkit based on PaddlePaddle. It.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1M" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 3K Β· πŸ“‹ 5.7K - 17% open Β· ⏱️ 10.10.2025):

    git clone https://github.com/PaddlePaddle/PaddleDetection
    
  • PyPi (πŸ“₯ 2.2K / month Β· πŸ“¦ 2 Β· ⏱️ 19.09.2022):

    pip install paddledet
    
</details> <details><summary><b><a href="https://github.com/ipazc/mtcnn">mtcnn</a></b> (πŸ₯‰27 Β· ⭐ 2.4K Β· πŸ’€) - MTCNN face detection implementation for TensorFlow, as a PIP.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 530 Β· πŸ“₯ 76 Β· πŸ“¦ 9.2K Β· πŸ“‹ 130 - 37% open Β· ⏱️ 08.10.2024):

    git clone https://github.com/ipazc/mtcnn
    
  • PyPi (πŸ“₯ 210K / month Β· πŸ“¦ 73 Β· ⏱️ 08.10.2024):

    pip install mtcnn
    
  • Conda (πŸ“₯ 16K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge mtcnn
    
</details> <details><summary><b><a href="https://github.com/CellProfiler/CellProfiler">CellProfiler</a></b> (πŸ₯‰27 Β· ⭐ 1.1K) - An open-source application for biological image analysis. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 410 Β· πŸ“₯ 24K Β· πŸ“¦ 28 Β· πŸ“‹ 3.4K - 10% open Β· ⏱️ 24.09.2025):

    git clone https://github.com/CellProfiler/CellProfiler
    
  • PyPi (πŸ“₯ 1.6K / month Β· πŸ“¦ 2 Β· ⏱️ 16.09.2024):

    pip install cellprofiler
    
</details> <details><summary><b><a href="https://github.com/luispedro/mahotas">mahotas</a></b> (πŸ₯‰27 Β· ⭐ 880) - Computer Vision in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 150 Β· πŸ“¦ 1.6K Β· πŸ“‹ 92 - 21% open Β· ⏱️ 05.08.2025):

    git clone https://github.com/luispedro/mahotas
    
  • PyPi (πŸ“₯ 42K / month Β· πŸ“¦ 63 Β· ⏱️ 17.07.2024):

    pip install mahotas
    
  • Conda (πŸ“₯ 790K Β· ⏱️ 21.10.2025):

    conda install -c conda-forge mahotas
    
</details> <details><summary><b><a href="https://github.com/idealo/imagededup">Image Deduplicator</a></b> (πŸ₯‰26 Β· ⭐ 5.5K) - Finding duplicate images made easy!. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 460 Β· πŸ“₯ 29 Β· πŸ“¦ 200 Β· πŸ“‹ 140 - 25% open Β· ⏱️ 15.08.2025):

    git clone https://github.com/idealo/imagededup
    
  • PyPi (πŸ“₯ 69K / month Β· πŸ“¦ 29 Β· ⏱️ 15.08.2025):

    pip install imagededup
    
</details> <details><summary><b><a href="https://github.com/tensorflow/graphics">tensorflow-graphics</a></b> (πŸ₯‰26 Β· ⭐ 2.8K Β· πŸ’€) - TensorFlow Graphics: Differentiable Graphics Layers.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 39 Β· πŸ”€ 370 Β· πŸ“‹ 240 - 60% open Β· ⏱️ 03.02.2025):

    git clone https://github.com/tensorflow/graphics
    
  • PyPi (πŸ“₯ 61K / month Β· πŸ“¦ 11 Β· ⏱️ 03.12.2021):

    pip install tensorflow-graphics
    
</details> <details><summary><b><a href="https://github.com/tryolabs/norfair">Norfair</a></b> (πŸ₯‰26 Β· ⭐ 2.5K) - Lightweight Python library for adding real-time multi-object tracking.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 260 Β· πŸ“₯ 360 Β· πŸ“¦ 340 Β· πŸ“‹ 180 - 16% open Β· ⏱️ 30.04.2025):

    git clone https://github.com/tryolabs/norfair
    
  • PyPi (πŸ“₯ 44K / month Β· πŸ“¦ 9 Β· ⏱️ 30.04.2025):

    pip install norfair
    
</details> <details><summary><b><a href="https://github.com/libvips/pyvips">pyvips</a></b> (πŸ₯‰26 Β· ⭐ 740) - python binding for libvips using cffi. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 53 Β· πŸ“¦ 1.2K Β· πŸ“‹ 670 - 29% open Β· ⏱️ 04.09.2025):

    git clone https://github.com/libvips/pyvips
    
  • PyPi (πŸ“₯ 190K / month Β· πŸ“¦ 94 Β· ⏱️ 28.04.2025):

    pip install pyvips
    
  • Conda (πŸ“₯ 260K Β· ⏱️ 04.09.2025):

    conda install -c conda-forge pyvips
    
</details> <details><summary><b><a href="https://github.com/facebookresearch/pytorchvideo">pytorchvideo</a></b> (πŸ₯‰25 Β· ⭐ 3.5K) - A deep learning library for video understanding research. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 59 Β· πŸ”€ 420 Β· πŸ“‹ 210 - 50% open Β· ⏱️ 27.10.2025):

    git clone https://github.com/facebookresearch/pytorchvideo
    
  • PyPi (πŸ“₯ 53K / month Β· πŸ“¦ 24 Β· ⏱️ 20.01.2022):

    pip install pytorchvideo
    
</details> <details><summary><b><a href="https://github.com/facebookresearch/mmf">MMF</a></b> (πŸ₯‰24 Β· ⭐ 5.6K) - A modular framework for vision & language multimodal research from.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 920 Β· πŸ“¦ 23 Β· πŸ“‹ 690 - 21% open Β· ⏱️ 24.04.2025):

    git clone https://github.com/facebookresearch/mmf
    
  • PyPi (πŸ“₯ 190 / month Β· πŸ“¦ 1 Β· ⏱️ 12.06.2020):

    pip install mmf
    
</details> <details><summary><b><a href="https://github.com/google-research/kubric">kubric</a></b> (πŸ₯‰22 Β· ⭐ 2.6K) - A data generation pipeline for creating semi-realistic synthetic.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 250 Β· πŸ“¦ 7 Β· πŸ“‹ 200 - 35% open Β· ⏱️ 06.05.2025):

    git clone https://github.com/google-research/kubric
    
  • PyPi (πŸ“₯ 6.6K / month Β· ⏱️ 27.12.2023):

    pip install kubric-nightly
    
</details> <details><summary><b><a href="https://github.com/airctic/icevision">icevision</a></b> (πŸ₯‰22 Β· ⭐ 870 Β· πŸ’€) - An Agnostic Computer Vision Framework - Pluggable to any.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 130 Β· πŸ“‹ 570 - 10% open Β· ⏱️ 31.10.2024):

    git clone https://github.com/airctic/icevision
    
  • PyPi (πŸ“₯ 2.3K / month Β· πŸ“¦ 6 Β· ⏱️ 10.02.2022):

    pip install icevision
    
</details> <details><summary><b><a href="https://github.com/facebookresearch/SlowFast">PySlowFast</a></b> (πŸ₯‰21 Β· ⭐ 7.2K) - PySlowFast: video understanding codebase from FAIR for.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 1.2K Β· πŸ“¦ 23 Β· πŸ“‹ 720 - 59% open Β· ⏱️ 27.10.2025):

    git clone https://github.com/facebookresearch/SlowFast
    
  • PyPi (πŸ“₯ 22 / month Β· ⏱️ 15.01.2020):

    pip install pyslowfast
    
</details> <details><summary><b><a href="https://github.com/idealo/image-super-resolution">Image Super-Resolution</a></b> (πŸ₯‰21 Β· ⭐ 4.8K Β· πŸ’€) - Super-scale your images and run experiments with.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 11 Β· πŸ”€ 760 Β· πŸ“‹ 220 - 48% open Β· ⏱️ 18.12.2024):

    git clone https://github.com/idealo/image-super-resolution
    
  • PyPi (πŸ“₯ 3.9K / month Β· πŸ“¦ 5 Β· ⏱️ 08.01.2020):

    pip install ISR
    
  • Docker Hub (πŸ“₯ 290 Β· ⭐ 1 Β· ⏱️ 01.04.2019):

    docker pull idealo/image-super-resolution-gpu
    
</details> <details><summary><b><a href="https://github.com/jasmcaus/caer">Caer</a></b> (πŸ₯‰21 Β· ⭐ 800) - A lightweight Computer Vision library. Scale your models, not boilerplate. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 8 Β· πŸ”€ 110 Β· πŸ“₯ 48 Β· ⏱️ 11.08.2025):

    git clone https://github.com/jasmcaus/caer
    
  • PyPi (πŸ“₯ 3.8K / month Β· πŸ“¦ 3 Β· ⏱️ 11.08.2025):

    pip install caer
    
</details> <details><summary><b><a href="https://github.com/google-research/scenic">scenic</a></b> (πŸ₯‰16 Β· ⭐ 3.7K) - Scenic: A Jax Library for Computer Vision Research and Beyond. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 95 Β· πŸ”€ 460 Β· πŸ“‹ 400 - 70% open Β· ⏱️ 06.08.2025):

    git clone https://github.com/google-research/scenic
    
</details> <details><summary>Show 30 hidden projects...</summary>
  • <b><a href="https://github.com/scikit-image/scikit-image">scikit-image</a></b> (πŸ₯‡41 Β· ⭐ 6.4K Β· πŸ“ˆ) - Image processing in Python. <code>❗Unlicensed</code>
  • <b><a href="https://github.com/glfw/glfw">glfw</a></b> (πŸ₯ˆ38 Β· ⭐ 14K) - A multi-platform library for OpenGL, OpenGL ES, Vulkan, window and input. <code><a href="https://tldrlegal.com/search?q=Zlib">❗️Zlib</a></code>
  • <b><a href="https://github.com/open-mmlab/mmdetection">MMDetection</a></b> (πŸ₯ˆ37 Β· ⭐ 32K Β· πŸ’€) - OpenMMLab Detection Toolbox and Benchmark. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/aleju/imgaug">imgaug</a></b> (πŸ₯ˆ36 Β· ⭐ 15K Β· πŸ’€) - Image augmentation for machine learning experiments. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/ageitgey/face_recognition">Face Recognition</a></b> (πŸ₯ˆ35 Β· ⭐ 56K Β· πŸ’€) - The worlds simplest facial recognition api for Python.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/PyImageSearch/imutils">imutils</a></b> (πŸ₯ˆ31 Β· ⭐ 4.6K Β· πŸ’€) - A series of convenience functions to make basic image processing.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/facebookresearch/pytorch3d">PyTorch3D</a></b> (πŸ₯ˆ30 Β· ⭐ 9.6K) - PyTorch3D is FAIRs library of reusable components for.. <code>❗Unlicensed</code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/OlafenwaMoses/ImageAI">imageai</a></b> (πŸ₯ˆ30 Β· ⭐ 8.8K Β· πŸ’€) - A python library built to empower developers to build applications.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/1adrianb/face-alignment">Face Alignment</a></b> (πŸ₯‰28 Β· ⭐ 7.4K Β· πŸ’€) - 2D and 3D Face alignment library build using pytorch. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/dmlc/gluon-cv">GluonCV</a></b> (πŸ₯‰27 Β· ⭐ 5.9K Β· πŸ’€) - Gluon CV Toolkit. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1X" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/mdbloice/Augmentor">Augmentor</a></b> (πŸ₯‰27 Β· ⭐ 5.1K Β· πŸ’€) - Image augmentation library in Python for machine learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/abhiTronix/vidgear">vidgear</a></b> (πŸ₯‰27 Β· ⭐ 3.6K Β· πŸ’€) - A High-performance cross-platform Video Processing Python.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/chainer/chainercv">chainercv</a></b> (πŸ₯‰27 Β· ⭐ 1.5K Β· πŸ’€) - ChainerCV: a Library for Deep Learning in Computer Vision. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/timesler/facenet-pytorch">facenet-pytorch</a></b> (πŸ₯‰26 Β· ⭐ 5K Β· πŸ’€) - Pretrained Pytorch face detection (MTCNN) and facial.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/uploadcare/pillow-simd">Pillow-SIMD</a></b> (πŸ₯‰25 Β· ⭐ 2.2K Β· πŸ’€) - The friendly PIL fork. <code><a href="https://tldrlegal.com/search?q=PIL">❗️PIL</a></code>
  • <b><a href="https://github.com/Layout-Parser/layout-parser">layout-parser</a></b> (πŸ₯‰24 Β· ⭐ 5.6K Β· πŸ’€) - A Unified Toolkit for Deep Learning Based Document Image.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/qubvel/segmentation_models">segmentation_models</a></b> (πŸ₯‰24 Β· ⭐ 4.9K Β· πŸ’€) - Segmentation models with pretrained backbones. Keras.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/libffcv/ffcv">ffcv</a></b> (πŸ₯‰23 Β· ⭐ 3K Β· πŸ’€) - FFCV: Fast Forward Computer Vision (and other ML workloads!). <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/facebookresearch/ClassyVision">Classy Vision</a></b> (πŸ₯‰23 Β· ⭐ 1.6K Β· πŸ’€) - An end-to-end PyTorch framework for image and video.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/lucidrains/deep-daze">deep-daze</a></b> (πŸ₯‰22 Β· ⭐ 4.3K Β· πŸ’€) - Simple command line tool for text to image generation using.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/facebookresearch/vissl">vissl</a></b> (πŸ₯‰22 Β· ⭐ 3.3K Β· πŸ’€) - VISSL is FAIRs library of extensible, modular and scalable.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/tryolabs/luminoth">Luminoth</a></b> (πŸ₯‰22 Β· ⭐ 2.4K Β· πŸ’€) - Deep Learning toolkit for Computer Vision. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/alankbi/detecto">detecto</a></b> (πŸ₯‰21 Β· ⭐ 620 Β· πŸ’€) - Build fully-functioning computer vision models with PyTorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/facebookresearch/detr">DEβ«ΆTR</a></b> (πŸ₯‰20 Β· ⭐ 15K Β· πŸ’€) - End-to-End Object Detection with Transformers. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/rhsimplex/image-match">image-match</a></b> (πŸ₯‰20 Β· ⭐ 3K Β· πŸ’€) - Quickly search over billions of images. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/imedslab/solt">solt</a></b> (πŸ₯‰19 Β· ⭐ 260) - Streaming over lightweight data transformations. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/facebookresearch/pycls">pycls</a></b> (πŸ₯‰18 Β· ⭐ 2.2K Β· πŸ’€) - Codebase for Image Classification Research, written in PyTorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/nicolas-chaulet/torch-points3d">Torch Points 3D</a></b> (πŸ₯‰17 Β· ⭐ 260 Β· πŸ’€) - Pytorch framework for doing deep learning on point.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/hhatto/nude.py">nude.py</a></b> (πŸ₯‰16 Β· ⭐ 920 Β· πŸ’€) - Nudity detection with Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/qanastek/HugsVision">HugsVision</a></b> (πŸ₯‰14 Β· ⭐ 200 Β· πŸ’€) - HugsVision is a easy to use huggingface wrapper for state-of-.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code>huggingface</code>
</details> <br>

Graph Data

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries for graph processing, clustering, embedding, and machine learning tasks.

<details><summary><b><a href="https://github.com/networkx/networkx">networkx</a></b> (πŸ₯‡46 Β· ⭐ 16K) - Network Analysis in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 790 Β· πŸ”€ 3.4K Β· πŸ“₯ 110 Β· πŸ“¦ 430K Β· πŸ“‹ 3.5K - 10% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/networkx/networkx
    
  • PyPi (πŸ“₯ 130M / month Β· πŸ“¦ 12K Β· ⏱️ 29.05.2025):

    pip install networkx
    
  • Conda (πŸ“₯ 26M Β· ⏱️ 04.06.2025):

    conda install -c conda-forge networkx
    
</details> <details><summary><b><a href="https://github.com/pyg-team/pytorch_geometric">PyTorch Geometric</a></b> (πŸ₯‡41 Β· ⭐ 23K) - Graph Neural Network Library for PyTorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 560 Β· πŸ”€ 3.9K Β· πŸ“¦ 11K Β· πŸ“‹ 4K - 30% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/pyg-team/pytorch_geometric
    
  • PyPi (πŸ“₯ 940K / month Β· πŸ“¦ 730 Β· ⏱️ 15.10.2025):

    pip install torch-geometric
    
  • Conda (πŸ“₯ 190K Β· ⏱️ 16.10.2025):

    conda install -c conda-forge pytorch_geometric
    
</details> <details><summary><b><a href="https://github.com/dmlc/dgl">dgl</a></b> (πŸ₯‡36 Β· ⭐ 14K) - Python package built to ease deep learning on graph, on top of existing DL.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 300 Β· πŸ”€ 3K Β· πŸ“¦ 4.1K Β· πŸ“‹ 3K - 20% open Β· ⏱️ 31.07.2025):

    git clone https://github.com/dmlc/dgl
    
  • PyPi (πŸ“₯ 150K / month Β· πŸ“¦ 150 Β· ⏱️ 13.05.2024):

    pip install dgl
    
</details> <details><summary><b><a href="https://github.com/graphistry/pygraphistry">pygraphistry</a></b> (πŸ₯ˆ29 Β· ⭐ 2.4K) - PyGraphistry is a Python library to quickly load, shape,.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 220 Β· πŸ“‹ 420 - 51% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/graphistry/pygraphistry
    
  • PyPi (πŸ“₯ 8.5K / month Β· πŸ“¦ 9 Β· ⏱️ 21.10.2025):

    pip install graphistry
    
</details> <details><summary><b><a href="https://github.com/snap-stanford/ogb">ogb</a></b> (πŸ₯ˆ29 Β· ⭐ 2K) - Benchmark datasets, data loaders, and evaluators for graph machine learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 32 Β· πŸ”€ 400 Β· πŸ“¦ 2.6K Β· πŸ“‹ 310 - 11% open Β· ⏱️ 06.05.2025):

    git clone https://github.com/snap-stanford/ogb
    
  • PyPi (πŸ“₯ 100K / month Β· πŸ“¦ 73 Β· ⏱️ 07.04.2023):

    pip install ogb
    
  • Conda (πŸ“₯ 63K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge ogb
    
</details> <details><summary><b><a href="https://github.com/pykeen/pykeen">PyKEEN</a></b> (πŸ₯ˆ28 Β· ⭐ 1.9K) - A Python library for learning and evaluating knowledge graph embeddings. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 210 Β· πŸ“₯ 240 Β· πŸ“¦ 350 Β· πŸ“‹ 590 - 20% open Β· ⏱️ 18.07.2025):

    git clone https://github.com/pykeen/pykeen
    
  • PyPi (πŸ“₯ 31K / month Β· πŸ“¦ 28 Β· ⏱️ 24.04.2025):

    pip install pykeen
    
</details> <details><summary><b><a href="https://github.com/benedekrozemberczki/pytorch_geometric_temporal">pytorch_geometric_temporal</a></b> (πŸ₯ˆ27 Β· ⭐ 2.9K) - PyTorch Geometric Temporal: Spatiotemporal Signal.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 39 Β· πŸ”€ 400 Β· πŸ“‹ 210 - 18% open Β· ⏱️ 18.09.2025):

    git clone https://github.com/benedekrozemberczki/pytorch_geometric_temporal
    
  • PyPi (πŸ“₯ 6.7K / month Β· πŸ“¦ 12 Β· ⏱️ 16.07.2025):

    pip install torch-geometric-temporal
    
</details> <details><summary><b><a href="https://github.com/rusty1s/pytorch_cluster">torch-cluster</a></b> (πŸ₯ˆ24 Β· ⭐ 900) - PyTorch Extension Library of Optimized Graph Cluster.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 150 Β· πŸ“‹ 190 - 16% open Β· ⏱️ 12.08.2025):

    git clone https://github.com/rusty1s/pytorch_cluster
    
  • PyPi (πŸ“₯ 34K / month Β· πŸ“¦ 62 Β· ⏱️ 12.10.2023):

    pip install torch-cluster
    
  • Conda (πŸ“₯ 440K Β· ⏱️ 22.09.2025):

    conda install -c conda-forge pytorch_cluster
    
</details> <details><summary>Show 28 hidden projects...</summary>
  • <b><a href="https://github.com/igraph/python-igraph">igraph</a></b> (πŸ₯‡34 Β· ⭐ 1.4K) - Python interface for igraph. <code><a href="http://bit.ly/2KucAZR">❗️GPL-2.0</a></code>
  • <b><a href="https://github.com/danielegrattarola/spektral">Spektral</a></b> (πŸ₯ˆ28 Β· ⭐ 2.4K Β· πŸ’€) - Graph Neural Networks with Keras and Tensorflow 2. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/stellargraph/stellargraph">StellarGraph</a></b> (πŸ₯ˆ27 Β· ⭐ 3K Β· πŸ’€) - StellarGraph - Machine Learning on Graphs. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/Kozea/pygal">pygal</a></b> (πŸ₯ˆ26 Β· ⭐ 2.7K Β· πŸ’€) - PYthon svg GrAph plotting Library. <code><a href="http://bit.ly/37RvQcA">❗️LGPL-3.0</a></code>
  • <b><a href="https://github.com/PaddlePaddle/PGL">Paddle Graph Learning</a></b> (πŸ₯ˆ26 Β· ⭐ 1.6K Β· πŸ’€) - Paddle Graph Learning (PGL) is an efficient and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1M" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/Accenture/AmpliGraph">AmpliGraph</a></b> (πŸ₯ˆ25 Β· ⭐ 2.2K Β· πŸ’€) - Python library for Representation Learning on Knowledge.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/eliorc/node2vec">Node2Vec</a></b> (πŸ₯ˆ25 Β· ⭐ 1.3K Β· πŸ’€) - Implementation of the node2vec algorithm. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/benedekrozemberczki/karateclub">Karate Club</a></b> (πŸ₯ˆ24 Β· ⭐ 2.3K Β· πŸ’€) - Karate Club: An API Oriented Open-source Python Framework.. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code>
  • <b><a href="https://github.com/google-deepmind/graph_nets">graph-nets</a></b> (πŸ₯‰22 Β· ⭐ 5.4K Β· πŸ’€) - Build Graph Nets in Tensorflow. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/facebookresearch/PyTorch-BigGraph">PyTorch-BigGraph</a></b> (πŸ₯‰21 Β· ⭐ 3.4K Β· πŸ’€) - Generate embeddings from large-scale graph-structured.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/graph4ai/graph4nlp">graph4nlp</a></b> (πŸ₯‰21 Β· ⭐ 1.7K Β· πŸ’€) - Graph4nlp is the library for the easy use of Graph.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/google-deepmind/jraph">jraph</a></b> (πŸ₯‰21 Β· ⭐ 1.5K Β· πŸ’€) - A Graph Neural Network Library in Jax. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/phanein/deepwalk">DeepWalk</a></b> (πŸ₯‰20 Β· ⭐ 2.7K Β· πŸ’€) - DeepWalk - Deep Learning for Graphs. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code>
  • <b><a href="https://github.com/divelab/DIG">DIG</a></b> (πŸ₯‰20 Β· ⭐ 2K Β· πŸ’€) - A library for graph deep learning research. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code>
  • <b><a href="https://github.com/snap-stanford/deepsnap">deepsnap</a></b> (πŸ₯‰20 Β· ⭐ 560 Β· πŸ’€) - Python library assists deep learning on graphs. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/predict-idlab/pyRDF2Vec">pyRDF2Vec</a></b> (πŸ₯‰20 Β· ⭐ 260 Β· πŸ’€) - Python Implementation and Extension of RDF2Vec. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/snap-stanford/GraphGym">GraphGym</a></b> (πŸ₯‰17 Β· ⭐ 1.8K Β· πŸ’€) - Platform for designing and evaluating Graph Neural Networks (GNN). <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/gsi-upm/sematch">Sematch</a></b> (πŸ₯‰17 Β· ⭐ 440 Β· πŸ’€) - semantic similarity framework for knowledge graph. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/deepgraph/deepgraph">DeepGraph</a></b> (πŸ₯‰17 Β· ⭐ 320) - Analyze Data with Pandas-based Networks. Documentation:. <code>❗Unlicensed</code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/THUMNLab/AutoGL">AutoGL</a></b> (πŸ₯‰16 Β· ⭐ 1.1K Β· πŸ’€) - An autoML framework & toolkit for machine learning on graphs. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/typedb/typedb-ml">kglib</a></b> (πŸ₯‰16 Β· ⭐ 550 Β· πŸ’€) - TypeDB-ML is the Machine Learning integrations library for TypeDB. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/microsoft/ptgnn">ptgnn</a></b> (πŸ₯‰16 Β· ⭐ 380 Β· πŸ’€) - A PyTorch Graph Neural Network Library. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/alibaba/euler">Euler</a></b> (πŸ₯‰15 Β· ⭐ 2.9K Β· πŸ’€) - A distributed graph deep learning framework. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/shenweichen/GraphEmbedding">GraphEmbedding</a></b> (πŸ₯‰14 Β· ⭐ 3.8K Β· πŸ’€) - Implementation and experiments of graph embedding.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/williamleif/GraphSAGE">GraphSAGE</a></b> (πŸ₯‰14 Β· ⭐ 3.6K Β· πŸ’€) - Representation learning on large graphs using stochastic.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/thunlp/OpenNE">OpenNE</a></b> (πŸ₯‰14 Β· ⭐ 1.7K Β· πŸ’€) - An Open-Source Package for Network Embedding (NE). <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/DeepGraphLearning/graphvite">GraphVite</a></b> (πŸ₯‰14 Β· ⭐ 1.3K Β· πŸ’€) - GraphVite: A General and High-performance Graph Embedding.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/thunlp/OpenKE">OpenKE</a></b> (πŸ₯‰13 Β· ⭐ 4K Β· πŸ’€) - An Open-Source Package for Knowledge Embedding (KE). <code>❗Unlicensed</code>
</details> <br>

Audio Data

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries for audio analysis, manipulation, transformation, and extraction, as well as speech recognition and music generation tasks.

<details><summary><b><a href="https://github.com/speechbrain/speechbrain">speechbrain</a></b> (πŸ₯‡38 Β· ⭐ 11K) - A PyTorch-based Speech Toolkit. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 1.5K Β· πŸ“¦ 3.9K Β· πŸ“‹ 1.2K - 12% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/speechbrain/speechbrain
    
  • PyPi (πŸ“₯ 1.1M / month Β· πŸ“¦ 79 Β· ⏱️ 07.04.2025):

    pip install speechbrain
    
</details> <details><summary><b><a href="https://github.com/espnet/espnet">espnet</a></b> (πŸ₯‡38 Β· ⭐ 9.5K) - End-to-End Speech Processing Toolkit. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 520 Β· πŸ”€ 2.3K Β· πŸ“₯ 84 Β· πŸ“¦ 480 Β· πŸ“‹ 2.5K - 3% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/espnet/espnet
    
  • PyPi (πŸ“₯ 24K / month Β· πŸ“¦ 19 Β· ⏱️ 13.09.2025):

    pip install espnet
    
</details> <details><summary><b><a href="https://github.com/pytorch/audio">torchaudio</a></b> (πŸ₯‡37 Β· ⭐ 2.8K) - Data manipulation and transformation for audio signal.. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 730 Β· πŸ“‹ 1.1K - 31% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/pytorch/audio
    
  • PyPi (πŸ“₯ 15M / month Β· πŸ“¦ 2.4K Β· ⏱️ 15.10.2025):

    pip install torchaudio
    
</details> <details><summary><b><a href="https://github.com/Uberi/speech_recognition">SpeechRecognition</a></b> (πŸ₯ˆ34 Β· ⭐ 8.9K) - Speech recognition module for Python, supporting several.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 2.4K Β· πŸ“¦ 21 Β· πŸ“‹ 670 - 48% open Β· ⏱️ 28.10.2025):

    git clone https://github.com/Uberi/speech_recognition
    
  • PyPi (πŸ“₯ 2.2M / month Β· πŸ“¦ 730 Β· ⏱️ 12.05.2025):

    pip install SpeechRecognition
    
  • Conda (πŸ“₯ 360K Β· ⏱️ 12.05.2025):

    conda install -c conda-forge speechrecognition
    
</details> <details><summary><b><a href="https://github.com/librosa/librosa">librosa</a></b> (πŸ₯ˆ34 Β· ⭐ 8K) - Python library for audio and music analysis. <code><a href="http://bit.ly/3hkKRql">ISC</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 1K Β· πŸ“‹ 1.3K - 5% open Β· ⏱️ 19.05.2025):

    git clone https://github.com/librosa/librosa
    
  • PyPi (πŸ“₯ 5.6M / month Β· πŸ“¦ 1.6K Β· ⏱️ 11.03.2025):

    pip install librosa
    
  • Conda (πŸ“₯ 1.1M Β· ⏱️ 22.04.2025):

    conda install -c conda-forge librosa
    
</details> <details><summary><b><a href="https://github.com/mozilla/DeepSpeech">DeepSpeech</a></b> (πŸ₯ˆ33 Β· ⭐ 27K Β· πŸ“ˆ) - DeepSpeech is an open source embedded (offline, on-.. <code><a href="http://bit.ly/3postzC">MPL-2.0</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 4.1K Β· πŸ“₯ 660K Β· πŸ“¦ 540 Β· πŸ“‹ 2.1K - 7% open Β· ⏱️ 19.06.2025):

    git clone https://github.com/mozilla/DeepSpeech
    
  • PyPi (πŸ“₯ 5.5K / month Β· πŸ“¦ 24 Β· ⏱️ 19.12.2020):

    pip install deepspeech
    
  • Conda (πŸ“₯ 4.2K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge deepspeech
    
</details> <details><summary><b><a href="https://github.com/beetbox/audioread">audioread</a></b> (πŸ₯ˆ33 Β· ⭐ 520 Β· πŸ“ˆ) - cross-library (GStreamer + Core Audio + MAD + FFmpeg) audio.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 110 Β· πŸ“¦ 35K Β· πŸ“‹ 98 - 40% open Β· ⏱️ 26.10.2025):

    git clone https://github.com/beetbox/audioread
    
  • PyPi (πŸ“₯ 4.8M / month Β· πŸ“¦ 180 Β· ⏱️ 26.10.2025):

    pip install audioread
    
  • Conda (πŸ“₯ 1.2M Β· ⏱️ 02.10.2025):

    conda install -c conda-forge audioread
    
</details> <details><summary><b><a href="https://github.com/deezer/spleeter">spleeter</a></b> (πŸ₯ˆ32 Β· ⭐ 27K) - Deezer source separation library including pretrained models. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 22 Β· πŸ”€ 3K Β· πŸ“₯ 4.4M Β· πŸ“¦ 1.1K Β· πŸ“‹ 830 - 32% open Β· ⏱️ 02.04.2025):

    git clone https://github.com/deezer/spleeter
    
  • PyPi (πŸ“₯ 26K / month Β· πŸ“¦ 18 Β· ⏱️ 03.04.2025):

    pip install spleeter
    
  • Conda (πŸ“₯ 120K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge spleeter
    
</details> <details><summary><b><a href="https://github.com/iver56/audiomentations">audiomentations</a></b> (πŸ₯ˆ32 Β· ⭐ 2.2K) - A Python library for audio data augmentation. Useful for.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 200 Β· πŸ“¦ 840 Β· πŸ“‹ 210 - 26% open Β· ⏱️ 26.09.2025):

    git clone https://github.com/iver56/audiomentations
    
  • PyPi (πŸ“₯ 110K / month Β· πŸ“¦ 38 Β· ⏱️ 13.09.2025):

    pip install audiomentations
    
</details> <details><summary><b><a href="https://github.com/idiap/coqui-ai-TTS">Coqui TTS</a></b> (πŸ₯ˆ32 Β· ⭐ 1.9K) - - a deep learning toolkit for Text-to-Speech, battle-.. <code><a href="http://bit.ly/3postzC">MPL-2.0</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 200 Β· πŸ”€ 240 Β· πŸ“₯ 3.8K Β· πŸ“¦ 760 Β· πŸ“‹ 160 - 14% open Β· ⏱️ 16.10.2025):

    git clone https://github.com/idiap/coqui-ai-TTS
    
  • PyPi (πŸ“₯ 94K / month Β· πŸ“¦ 34 Β· ⏱️ 25.09.2025):

    pip install coqui-tts
    
</details> <details><summary><b><a href="https://github.com/magenta/magenta">Magenta</a></b> (πŸ₯ˆ31 Β· ⭐ 20K) - Magenta: Music and Art Generation with Machine Intelligence. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 3.7K Β· πŸ“¦ 600 Β· πŸ“‹ 1K - 41% open Β· ⏱️ 08.07.2025):

    git clone https://github.com/magenta/magenta
    
  • PyPi (πŸ“₯ 4.8K / month Β· πŸ“¦ 5 Β· ⏱️ 01.08.2022):

    pip install magenta
    
</details> <details><summary><b><a href="https://github.com/Picovoice/porcupine">Porcupine</a></b> (πŸ₯‰29 Β· ⭐ 4.5K) - On-device wake word detection powered by deep learning. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 550 Β· πŸ“¦ 51 Β· πŸ“‹ 600 - 0% open Β· ⏱️ 17.10.2025):

    git clone https://github.com/Picovoice/Porcupine
    
  • PyPi (πŸ“₯ 25K / month Β· πŸ“¦ 38 Β· ⏱️ 05.02.2025):

    pip install pvporcupine
    
</details> <details><summary><b><a href="https://github.com/tyiannak/pyAudioAnalysis">pyAudioAnalysis</a></b> (πŸ₯‰28 Β· ⭐ 6.2K) - Python Audio Analysis Library: Feature Extraction,.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 1.2K Β· πŸ“¦ 670 Β· πŸ“‹ 330 - 62% open Β· ⏱️ 04.08.2025):

    git clone https://github.com/tyiannak/pyAudioAnalysis
    
  • PyPi (πŸ“₯ 24K / month Β· πŸ“¦ 12 Β· ⏱️ 07.02.2022):

    pip install pyAudioAnalysis
    
</details> <details><summary><b><a href="https://github.com/bastibe/python-soundfile">python-soundfile</a></b> (πŸ₯‰27 Β· ⭐ 800) - SoundFile is an audio library based on libsndfile, CFFI, and.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 120 Β· πŸ“₯ 21K Β· πŸ“‹ 260 - 46% open Β· ⏱️ 28.04.2025):

    git clone https://github.com/bastibe/python-soundfile
    
  • PyPi (πŸ“₯ 9.5M / month Β· πŸ“¦ 1.1K Β· ⏱️ 25.01.2025):

    pip install soundfile
    
  • Conda:

    conda install -c anaconda pysoundfile
    
</details> <details><summary><b><a href="https://github.com/tinytag/tinytag">tinytag</a></b> (πŸ₯‰27 Β· ⭐ 780) - Python library for reading audio file metadata. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 100 Β· πŸ“¦ 1.3K Β· πŸ“‹ 120 - 4% open Β· ⏱️ 13.08.2025):

    git clone https://github.com/devsnd/tinytag
    
  • PyPi (πŸ“₯ 120K / month Β· πŸ“¦ 130 Β· ⏱️ 13.08.2025):

    pip install tinytag
    
</details> <details><summary><b><a href="https://github.com/keunwoochoi/kapre">kapre</a></b> (πŸ₯‰25 Β· ⭐ 930 Β· πŸ“ˆ) - kapre: Keras Audio Preprocessors. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 150 Β· πŸ“₯ 33 Β· πŸ“¦ 2.5K Β· πŸ“‹ 99 - 17% open Β· ⏱️ 26.10.2025):

    git clone https://github.com/keunwoochoi/kapre
    
  • PyPi (πŸ“₯ 3.2K / month Β· πŸ“¦ 11 Β· ⏱️ 26.10.2025):

    pip install kapre
    
</details> <details><summary><b><a href="https://github.com/KinWaiCheuk/nnAudio">nnAudio</a></b> (πŸ₯‰22 Β· ⭐ 1.1K) - Audio processing by using pytorch 1D convolution network. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 96 Β· πŸ“¦ 410 Β· πŸ“‹ 65 - 30% open Β· ⏱️ 16.05.2025):

    git clone https://github.com/KinWaiCheuk/nnAudio
    
  • PyPi (πŸ“₯ 59K / month Β· πŸ“¦ 4 Β· ⏱️ 13.02.2024):

    pip install nnAudio
    
</details> <details><summary><b><a href="https://github.com/adefossez/julius">Julius</a></b> (πŸ₯‰21 Β· ⭐ 450 Β· πŸ’€) - Fast PyTorch based DSP for audio and 1D signals. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 3 Β· πŸ”€ 26 Β· πŸ“‹ 12 - 16% open Β· ⏱️ 17.02.2025):

    git clone https://github.com/adefossez/julius
    
  • PyPi (πŸ“₯ 840K / month Β· πŸ“¦ 44 Β· ⏱️ 20.09.2022):

    pip install julius
    
</details> <details><summary>Show 11 hidden projects...</summary>
  • <b><a href="https://github.com/jiaaro/pydub">Pydub</a></b> (πŸ₯ˆ36 Β· ⭐ 9.6K Β· πŸ’€) - Manipulate audio with a simple and easy high level interface. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/aubio/aubio">aubio</a></b> (πŸ₯‰27 Β· ⭐ 3.5K) - a library for audio and music analysis. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code>
  • <b><a href="https://github.com/MTG/essentia">Essentia</a></b> (πŸ₯‰27 Β· ⭐ 3.3K) - C++ library for audio and music analysis, description and.. <code><a href="http://bit.ly/3pwmjO5">❗️AGPL-3.0</a></code>
  • <b><a href="https://github.com/CPJKU/madmom">Madmom</a></b> (πŸ₯‰27 Β· ⭐ 1.5K Β· πŸ’€) - Python audio and music signal processing library. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/mozilla/TTS">TTS</a></b> (πŸ₯‰26 Β· ⭐ 10K Β· πŸ’€) - Deep learning for Text to Speech (Discussion forum:.. <code><a href="http://bit.ly/3postzC">MPL-2.0</a></code>
  • <b><a href="https://github.com/jameslyons/python_speech_features">python_speech_features</a></b> (πŸ₯‰26 Β· ⭐ 2.4K Β· πŸ’€) - This library provides common speech features for ASR.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/magenta/ddsp">DDSP</a></b> (πŸ₯‰25 Β· ⭐ 3.1K Β· πŸ’€) - DDSP: Differentiable Digital Signal Processing. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/worldveil/dejavu">Dejavu</a></b> (πŸ₯‰23 Β· ⭐ 6.7K Β· πŸ’€) - Audio fingerprinting and recognition in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/Parisson/TimeSide">TimeSide</a></b> (πŸ₯‰21 Β· ⭐ 390 Β· πŸ’€) - scalable audio processing framework and server written in.. <code><a href="http://bit.ly/3pwmjO5">❗️AGPL-3.0</a></code>
  • <b><a href="https://github.com/bmcfee/muda">Muda</a></b> (πŸ₯‰18 Β· ⭐ 240 Β· πŸ’€) - A library for augmenting annotated audio data. <code><a href="http://bit.ly/3hkKRql">ISC</a></code>
  • <b><a href="https://github.com/facebookresearch/textlesslib">textlesslib</a></b> (πŸ₯‰10 Β· ⭐ 550 Β· πŸ’€) - Library for Textless Spoken Language Processing. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
</details> <br>

Geospatial Data

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries to load, process, analyze, and write geographic data as well as libraries for spatial analysis, map visualization, and geocoding.

<details><summary><b><a href="https://github.com/visgl/deck.gl">pydeck</a></b> (πŸ₯‡43 Β· ⭐ 14K) - WebGL2 powered visualization framework. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 310 Β· πŸ”€ 2.2K Β· πŸ“¦ 9.2K Β· πŸ“‹ 3.3K - 13% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/visgl/deck.gl
    
  • PyPi (πŸ“₯ 16M / month Β· πŸ“¦ 160 Β· ⏱️ 21.03.2025):

    pip install pydeck
    
  • Conda (πŸ“₯ 850K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge pydeck
    
  • npm (πŸ“₯ 750K / month Β· πŸ“¦ 360 Β· ⏱️ 16.10.2025):

    npm install deck.gl
    
</details> <details><summary><b><a href="https://github.com/python-visualization/folium">folium</a></b> (πŸ₯‡40 Β· ⭐ 7.3K) - Python Data. Leaflet.js Maps. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 2.2K Β· πŸ“¦ 65K Β· πŸ“‹ 1.2K - 6% open Β· ⏱️ 06.10.2025):

    git clone https://github.com/python-visualization/folium
    
  • PyPi (πŸ“₯ 2.8M / month Β· πŸ“¦ 1K Β· ⏱️ 16.06.2025):

    pip install folium
    
  • Conda (πŸ“₯ 4.4M Β· ⏱️ 16.06.2025):

    conda install -c conda-forge folium
    
</details> <details><summary><b><a href="https://github.com/shapely/shapely">Shapely</a></b> (πŸ₯‡40 Β· ⭐ 4.3K) - Manipulation and analysis of geometric objects. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 600 Β· πŸ“₯ 4K Β· πŸ“¦ 110K Β· πŸ“‹ 1.3K - 18% open Β· ⏱️ 28.10.2025):

    git clone https://github.com/shapely/shapely
    
  • PyPi (πŸ“₯ 62M / month Β· πŸ“¦ 4.7K Β· ⏱️ 24.09.2025):

    pip install shapely
    
  • Conda (πŸ“₯ 14M Β· ⏱️ 28.10.2025):

    conda install -c conda-forge shapely
    
</details> <details><summary><b><a href="https://github.com/geopandas/geopandas">GeoPandas</a></b> (πŸ₯ˆ39 Β· ⭐ 4.9K) - Python tools for geographic data. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 250 Β· πŸ”€ 980 Β· πŸ“₯ 3.1K Β· πŸ“¦ 60K Β· πŸ“‹ 1.8K - 24% open Β· ⏱️ 25.10.2025):

    git clone https://github.com/geopandas/geopandas
    
  • PyPi (πŸ“₯ 11M / month Β· πŸ“¦ 3.8K Β· ⏱️ 26.06.2025):

    pip install geopandas
    
  • Conda (πŸ“₯ 5.4M Β· ⏱️ 06.10.2025):

    conda install -c conda-forge geopandas
    
</details> <details><summary><b><a href="https://github.com/rasterio/rasterio">Rasterio</a></b> (πŸ₯ˆ37 Β· ⭐ 2.4K) - Rasterio reads and writes geospatial raster datasets. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 540 Β· πŸ“₯ 1K Β· πŸ“¦ 19K Β· πŸ“‹ 1.9K - 8% open Β· ⏱️ 26.09.2025):

    git clone https://github.com/rasterio/rasterio
    
  • PyPi (πŸ“₯ 2.8M / month Β· πŸ“¦ 1.5K Β· ⏱️ 02.12.2024):

    pip install rasterio
    
  • Conda (πŸ“₯ 5.3M Β· ⏱️ 17.09.2025):

    conda install -c conda-forge rasterio
    
</details> <details><summary><b><a href="https://github.com/pyproj4/pyproj">pyproj</a></b> (πŸ₯ˆ37 Β· ⭐ 1.2K) - Python interface to PROJ (cartographic projections and coordinate.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 74 Β· πŸ”€ 230 Β· πŸ“¦ 47K Β· πŸ“‹ 660 - 6% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/pyproj4/pyproj
    
  • PyPi (πŸ“₯ 14M / month Β· πŸ“¦ 2.3K Β· ⏱️ 14.08.2025):

    pip install pyproj
    
  • Conda (πŸ“₯ 12M Β· ⏱️ 15.09.2025):

    conda install -c conda-forge pyproj
    
</details> <details><summary><b><a href="https://github.com/Esri/arcgis-python-api">ArcGIS API</a></b> (πŸ₯ˆ36 Β· ⭐ 2.1K) - Documentation and samples for ArcGIS API for Python. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 99 Β· πŸ”€ 1.1K Β· πŸ“₯ 16K Β· πŸ“¦ 1K Β· πŸ“‹ 920 - 8% open Β· ⏱️ 28.10.2025):

    git clone https://github.com/Esri/arcgis-python-api
    
  • PyPi (πŸ“₯ 150K / month Β· πŸ“¦ 44 Β· ⏱️ 27.10.2025):

    pip install arcgis
    
  • Docker Hub:

    docker pull esridocker/arcgis-api-python-notebook
    
</details> <details><summary><b><a href="https://github.com/Toblerity/Fiona">Fiona</a></b> (πŸ₯ˆ34 Β· ⭐ 1.2K Β· πŸ’€) - Fiona reads and writes geographic data files. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 78 Β· πŸ”€ 210 Β· πŸ“¦ 27K Β· πŸ“‹ 820 - 5% open Β· ⏱️ 20.02.2025):

    git clone https://github.com/Toblerity/Fiona
    
  • PyPi (πŸ“₯ 5.6M / month Β· πŸ“¦ 380 Β· ⏱️ 16.09.2024):

    pip install fiona
    
  • Conda (πŸ“₯ 7.9M Β· ⏱️ 22.04.2025):

    conda install -c conda-forge fiona
    
</details> <details><summary><b><a href="https://github.com/jupyter-widgets/ipyleaflet">ipyleaflet</a></b> (πŸ₯‰33 Β· ⭐ 1.5K) - A Jupyter - Leaflet.js bridge. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 94 Β· πŸ”€ 360 Β· πŸ“¦ 18K Β· πŸ“‹ 660 - 44% open Β· ⏱️ 19.06.2025):

    git clone https://github.com/jupyter-widgets/ipyleaflet
    
  • PyPi (πŸ“₯ 230K / month Β· πŸ“¦ 340 Β· ⏱️ 13.06.2025):

    pip install ipyleaflet
    
  • Conda (πŸ“₯ 1.8M Β· ⏱️ 13.06.2025):

    conda install -c conda-forge ipyleaflet
    
  • npm (πŸ“₯ 2.7K / month Β· πŸ“¦ 9 Β· ⏱️ 13.06.2025):

    npm install jupyter-leaflet
    
</details> <details><summary><b><a href="https://github.com/jazzband/geojson">geojson</a></b> (πŸ₯‰31 Β· ⭐ 970 Β· πŸ’€) - Python bindings and utilities for GeoJSON. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 58 Β· πŸ”€ 120 Β· πŸ“¦ 21K Β· πŸ“‹ 100 - 26% open Β· ⏱️ 21.12.2024):

    git clone https://github.com/jazzband/geojson
    
  • PyPi (πŸ“₯ 3.6M / month Β· πŸ“¦ 720 Β· ⏱️ 21.12.2024):

    pip install geojson
    
  • Conda (πŸ“₯ 1.1M Β· ⏱️ 22.04.2025):

    conda install -c conda-forge geojson
    
</details> <details><summary><b><a href="https://github.com/pysal/pysal">PySAL</a></b> (πŸ₯‰30 Β· ⭐ 1.4K) - PySAL: Python Spatial Analysis Library Meta-Package. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 79 Β· πŸ”€ 310 Β· πŸ“¦ 1.8K Β· πŸ“‹ 660 - 3% open Β· ⏱️ 08.09.2025):

    git clone https://github.com/pysal/pysal
    
  • PyPi (πŸ“₯ 42K / month Β· πŸ“¦ 65 Β· ⏱️ 31.07.2025):

    pip install pysal
    
  • Conda (πŸ“₯ 730K Β· ⏱️ 01.08.2025):

    conda install -c conda-forge pysal
    
</details> <details><summary><b><a href="https://github.com/holoviz/geoviews">GeoViews</a></b> (πŸ₯‰28 Β· ⭐ 620) - Simple, concise geographical visualization in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 79 Β· πŸ“¦ 5 Β· πŸ“‹ 360 - 31% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/holoviz/geoviews
    
  • PyPi (πŸ“₯ 69K / month Β· πŸ“¦ 76 Β· ⏱️ 14.08.2025):

    pip install geoviews
    
  • Conda (πŸ“₯ 340K Β· ⏱️ 14.08.2025):

    conda install -c conda-forge geoviews
    
</details> <details><summary><b><a href="https://github.com/earthlab/earthpy">EarthPy</a></b> (πŸ₯‰28 Β· ⭐ 530) - A package built to support working with spatial data using open source.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 160 Β· πŸ“₯ 75 Β· πŸ“¦ 440 Β· πŸ“‹ 250 - 16% open Β· ⏱️ 31.07.2025):

    git clone https://github.com/earthlab/earthpy
    
  • PyPi (πŸ“₯ 14K / month Β· πŸ“¦ 17 Β· ⏱️ 01.10.2021):

    pip install earthpy
    
  • Conda (πŸ“₯ 98K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge earthpy
    
</details> <details><summary><b><a href="https://github.com/geospace-code/pymap3d">pymap3d</a></b> (πŸ₯‰25 Β· ⭐ 430) - pure-Python (Numpy optional) 3D coordinate conversions for geospace ecef.. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 87 Β· πŸ“¦ 540 Β· πŸ“‹ 59 - 8% open Β· ⏱️ 08.07.2025):

    git clone https://github.com/geospace-code/pymap3d
    
  • PyPi (πŸ“₯ 490K / month Β· πŸ“¦ 50 Β· ⏱️ 08.07.2025):

    pip install pymap3d
    
  • Conda (πŸ“₯ 120K Β· ⏱️ 08.07.2025):

    conda install -c conda-forge pymap3d
    
</details> <details><summary><b><a href="https://github.com/mapbox/mapboxgl-jupyter">Mapbox GL</a></b> (πŸ₯‰22 Β· ⭐ 680 Β· πŸ’€) - Use Mapbox GL JS to visualize data in a Python Jupyter notebook. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 140 Β· πŸ“‹ 110 - 38% open Β· ⏱️ 06.02.2025):

    git clone https://github.com/mapbox/mapboxgl-jupyter
    
  • PyPi (πŸ“₯ 10K / month Β· πŸ“¦ 12 Β· ⏱️ 02.06.2019):

    pip install mapboxgl
    
</details> <details><summary>Show 7 hidden projects...</summary>
  • <b><a href="https://github.com/pytroll/satpy">Satpy</a></b> (πŸ₯ˆ34 Β· ⭐ 1.1K) - Python package for earth-observing satellite data processing. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code>
  • <b><a href="https://github.com/geopy/geopy">geopy</a></b> (πŸ₯‰32 Β· ⭐ 4.7K Β· πŸ’€) - Geocoding library for Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/DenisCarriere/geocoder">Geocoder</a></b> (πŸ₯‰32 Β· ⭐ 1.6K Β· πŸ’€) - Python Geocoder. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/marceloprates/prettymaps">prettymaps</a></b> (πŸ₯‰24 Β· ⭐ 12K) - Draw pretty maps from OpenStreetMap data! Built with osmnx.. <code><a href="http://bit.ly/3pwmjO5">❗️AGPL-3.0</a></code>
  • <b><a href="https://github.com/sentinelsat/sentinelsat">Sentinelsat</a></b> (πŸ₯‰24 Β· ⭐ 1K Β· πŸ’€) - Search and download Copernicus Sentinel satellite images. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code>
  • <b><a href="https://github.com/pbugnion/gmaps">gmaps</a></b> (πŸ₯‰22 Β· ⭐ 760 Β· πŸ’€) - Google maps for Jupyter notebooks. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/andrea-cuttone/geoplotlib">geoplotlib</a></b> (πŸ₯‰21 Β· ⭐ 1K Β· πŸ’€) - python toolbox for visualizing geographical data and making maps. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
</details> <br>

Financial Data

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, technical analysis, and other tasks on financial data.

<details><summary><b><a href="https://github.com/ranaroussi/yfinance">yfinance</a></b> (πŸ₯‡42 Β· ⭐ 20K) - Download market data from Yahoo! Finances API. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 2.8K Β· πŸ“¦ 86K Β· πŸ“‹ 1.7K - 9% open Β· ⏱️ 18.09.2025):

    git clone https://github.com/ranaroussi/yfinance
    
  • PyPi (πŸ“₯ 5.9M / month Β· πŸ“¦ 1.2K Β· ⏱️ 17.09.2025):

    pip install yfinance
    
  • Conda (πŸ“₯ 99K Β· ⏱️ 25.03.2025):

    conda install -c ranaroussi yfinance
    
</details> <details><summary><b><a href="https://github.com/microsoft/qlib">Qlib</a></b> (πŸ₯‡32 Β· ⭐ 33K) - Qlib is an AI-oriented Quant investment platform that aims to use AI tech.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 5K Β· πŸ“₯ 910 Β· πŸ“¦ 21 Β· πŸ“‹ 1K - 28% open Β· ⏱️ 17.10.2025):

    git clone https://github.com/microsoft/qlib
    
  • PyPi (πŸ“₯ 16K / month Β· πŸ“¦ 3 Β· ⏱️ 15.08.2025):

    pip install pyqlib
    
</details> <details><summary><b><a href="https://github.com/pmorissette/bt">bt</a></b> (πŸ₯ˆ30 Β· ⭐ 2.7K) - bt - flexible backtesting for Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 450 Β· πŸ“¦ 1.7K Β· πŸ“‹ 350 - 23% open Β· ⏱️ 27.10.2025):

    git clone https://github.com/pmorissette/bt
    
  • PyPi (πŸ“₯ 11K / month Β· πŸ“¦ 15 Β· ⏱️ 12.04.2025):

    pip install bt
    
  • Conda (πŸ“₯ 110K Β· ⏱️ 02.10.2025):

    conda install -c conda-forge bt
    
</details> <details><summary><b><a href="https://github.com/RomelTorres/alpha_vantage">Alpha Vantage</a></b> (πŸ₯ˆ27 Β· ⭐ 4.6K) - A python wrapper for Alpha Vantage API for financial data. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 44 Β· πŸ”€ 760 Β· πŸ“‹ 290 - 0% open Β· ⏱️ 27.07.2025):

    git clone https://github.com/RomelTorres/alpha_vantage
    
  • PyPi (πŸ“₯ 140K / month Β· πŸ“¦ 35 Β· ⏱️ 18.07.2024):

    pip install alpha_vantage
    
  • Conda (πŸ“₯ 10K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge alpha_vantage
    
</details> <details><summary><b><a href="https://github.com/pmorissette/ffn">ffn</a></b> (πŸ₯ˆ27 Β· ⭐ 2.4K) - ffn - a financial function library for Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 330 Β· πŸ“¦ 580 Β· πŸ“‹ 140 - 17% open Β· ⏱️ 27.10.2025):

    git clone https://github.com/pmorissette/ffn
    
  • PyPi (πŸ“₯ 25K / month Β· πŸ“¦ 22 Β· ⏱️ 11.02.2025):

    pip install ffn
    
  • Conda (πŸ“₯ 26K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge ffn
    
</details> <details><summary><b><a href="https://github.com/jealous/stockstats">stockstats</a></b> (πŸ₯‰26 Β· ⭐ 1.4K) - Supply a wrapper ``StockDataFrame`` based on the.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 310 Β· πŸ“¦ 1.3K Β· πŸ“‹ 130 - 10% open Β· ⏱️ 18.05.2025):

    git clone https://github.com/jealous/stockstats
    
  • PyPi (πŸ“₯ 51K / month Β· πŸ“¦ 14 Β· ⏱️ 18.05.2025):

    pip install stockstats
    
</details> <details><summary><b><a href="https://github.com/google/tf-quant-finance">tf-quant-finance</a></b> (πŸ₯‰21 Β· ⭐ 5K Β· πŸ’€) - High-performance TensorFlow library for quantitative.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 630 Β· πŸ“‹ 65 - 56% open Β· ⏱️ 21.03.2025):

    git clone https://github.com/google/tf-quant-finance
    
  • PyPi (πŸ“₯ 410 / month Β· πŸ“¦ 3 Β· ⏱️ 19.08.2022):

    pip install tf-quant-finance
    
</details> <details><summary><b><a href="https://github.com/cuemacro/finmarketpy">finmarketpy</a></b> (πŸ₯‰21 Β· ⭐ 3.7K Β· πŸ’€) - Python library for backtesting trading strategies &.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 510 Β· πŸ“₯ 57 Β· πŸ“¦ 16 Β· πŸ“‹ 35 - 88% open Β· ⏱️ 10.03.2025):

    git clone https://github.com/cuemacro/finmarketpy
    
  • PyPi (πŸ“₯ 340 / month Β· ⏱️ 10.03.2025):

    pip install finmarketpy
    
</details> <details><summary>Show 17 hidden projects...</summary>
  • <b><a href="https://github.com/bashtage/arch">arch</a></b> (πŸ₯‡33 Β· ⭐ 1.5K) - ARCH models in Python. <code>❗Unlicensed</code>
  • <b><a href="https://github.com/quantopian/zipline">zipline</a></b> (πŸ₯‡32 Β· ⭐ 19K Β· πŸ’€) - Zipline, a Pythonic Algorithmic Trading Library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/bukosabino/ta">ta</a></b> (πŸ₯‡32 Β· ⭐ 4.8K Β· πŸ’€) - Technical Analysis Library using Pandas and Numpy. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/quantopian/pyfolio">pyfolio</a></b> (πŸ₯ˆ31 Β· ⭐ 6.1K Β· πŸ’€) - Portfolio and risk analytics in Python. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/mementum/backtrader">backtrader</a></b> (πŸ₯ˆ29 Β· ⭐ 19K Β· πŸ’€) - Python Backtesting library for trading strategies. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code>
  • <b><a href="https://github.com/erdewit/ib_insync">IB-insync</a></b> (πŸ₯ˆ28 Β· ⭐ 3.1K Β· πŸ’€) - Python sync/async framework for Interactive Brokers API. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code>
  • <b><a href="https://github.com/quantopian/alphalens">Alphalens</a></b> (πŸ₯ˆ27 Β· ⭐ 4K Β· πŸ’€) - Performance analysis of predictive (alpha) stock factors. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/scrtlabs/catalyst">Enigma Catalyst</a></b> (πŸ₯ˆ27 Β· ⭐ 2.5K Β· πŸ’€) - An Algorithmic Trading Library for Crypto-Assets in.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/quantopian/empyrical">empyrical</a></b> (πŸ₯ˆ27 Β· ⭐ 1.4K Β· πŸ’€) - Common financial risk and performance metrics. Used by.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/kernc/backtesting.py">Backtesting.py</a></b> (πŸ₯‰26 Β· ⭐ 7.4K) - Backtest trading strategies in Python. <code><a href="http://bit.ly/3pwmjO5">❗️AGPL-3.0</a></code>
  • <b><a href="https://github.com/tensortrade-org/tensortrade">TensorTrade</a></b> (πŸ₯‰26 Β· ⭐ 5.6K Β· πŸ’€) - An open source reinforcement learning framework for.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/gbeced/pyalgotrade">PyAlgoTrade</a></b> (πŸ₯‰25 Β· ⭐ 4.6K Β· πŸ’€) - Python Algorithmic Trading Library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/peerchemist/finta">FinTA</a></b> (πŸ₯‰24 Β· ⭐ 2.2K Β· πŸ’€) - Common financial technical indicators implemented in Pandas. <code><a href="http://bit.ly/37RvQcA">❗️LGPL-3.0</a></code>
  • <b><a href="https://github.com/CryptoSignal/Crypto-Signal">Crypto Signals</a></b> (πŸ₯‰22 Β· ⭐ 5.4K Β· πŸ’€) - Github.com/CryptoSignal - Trading & Technical Analysis Bot -.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/fmilthaler/FinQuant">FinQuant</a></b> (πŸ₯‰22 Β· ⭐ 1.6K Β· πŸ’€) - A program for financial portfolio management, analysis and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/tradytics/surpriver">surpriver</a></b> (πŸ₯‰12 Β· ⭐ 1.8K Β· πŸ’€) - Find big moving stocks before they move using machine.. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code>
  • <b><a href="https://github.com/alvarobartt/pyrtfolio">pyrtfolio</a></b> (πŸ₯‰9 Β· ⭐ 150 Β· πŸ’€) - Python package to generate stock portfolios. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code>
</details> <br>

Time Series Data

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries for forecasting, anomaly detection, feature extraction, and machine learning on time-series and sequential data.

<details><summary><b><a href="https://github.com/sktime/sktime">sktime</a></b> (πŸ₯‡41 Β· ⭐ 9.3K) - A unified framework for machine learning with time series. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 520 Β· πŸ”€ 1.7K Β· πŸ“₯ 110 Β· πŸ“¦ 4.7K Β· πŸ“‹ 3.1K - 39% open Β· ⏱️ 28.10.2025):

    git clone https://github.com/alan-turing-institute/sktime
    
  • PyPi (πŸ“₯ 1M / month Β· πŸ“¦ 160 Β· ⏱️ 25.09.2025):

    pip install sktime
    
  • Conda (πŸ“₯ 1.2M Β· ⏱️ 18.09.2025):

    conda install -c conda-forge sktime-all-extras
    
</details> <details><summary><b><a href="https://github.com/facebook/prophet">Prophet</a></b> (πŸ₯‡34 Β· ⭐ 20K) - Tool for producing high quality forecasts for time series data that has.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 4.6K Β· πŸ“₯ 3.2K Β· πŸ“¦ 21 Β· πŸ“‹ 2.2K - 20% open Β· ⏱️ 21.10.2025):

    git clone https://github.com/facebook/prophet
    
  • PyPi (πŸ“₯ 84K / month Β· πŸ“¦ 91 Β· ⏱️ 05.09.2020):

    pip install fbprophet
    
  • Conda (πŸ“₯ 1.5M Β· ⏱️ 22.10.2025):

    conda install -c conda-forge prophet
    
</details> <details><summary><b><a href="https://github.com/Nixtla/statsforecast">StatsForecast</a></b> (πŸ₯‡34 Β· ⭐ 4.6K) - Lightning fast forecasting with statistical and econometric.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 56 Β· πŸ”€ 340 Β· πŸ“¦ 2K Β· πŸ“‹ 400 - 34% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/Nixtla/statsforecast
    
  • PyPi (πŸ“₯ 990K / month Β· πŸ“¦ 91 Β· ⏱️ 29.10.2025):

    pip install statsforecast
    
  • Conda (πŸ“₯ 220K Β· ⏱️ 30.10.2025):

    conda install -c conda-forge statsforecast
    
</details> <details><summary><b><a href="https://github.com/tslearn-team/tslearn">tslearn</a></b> (πŸ₯ˆ33 Β· ⭐ 3.1K) - The machine learning toolkit for time series analysis in Python. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 350 Β· πŸ“¦ 1.9K Β· πŸ“‹ 380 - 38% open Β· ⏱️ 27.10.2025):

    git clone https://github.com/tslearn-team/tslearn
    
  • PyPi (πŸ“₯ 400K / month Β· πŸ“¦ 110 Β· ⏱️ 02.07.2025):

    pip install tslearn
    
  • Conda (πŸ“₯ 1.7M Β· ⏱️ 03.07.2025):

    conda install -c conda-forge tslearn
    
</details> <details><summary><b><a href="https://github.com/skforecast/skforecast">skforecast</a></b> (πŸ₯ˆ33 Β· ⭐ 1.4K) - Time series forecasting with machine learning models. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 170 Β· πŸ“¦ 490 Β· πŸ“‹ 210 - 8% open Β· ⏱️ 22.09.2025):

    git clone https://github.com/JoaquinAmatRodrigo/skforecast
    
  • PyPi (πŸ“₯ 96K / month Β· πŸ“¦ 18 Β· ⏱️ 22.09.2025):

    pip install skforecast
    
</details> <details><summary><b><a href="https://github.com/unit8co/darts">Darts</a></b> (πŸ₯ˆ32 Β· ⭐ 9K) - A python library for user-friendly forecasting and anomaly detection on.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 970 Β· πŸ“‹ 1.8K - 13% open Β· ⏱️ 26.10.2025):

    git clone https://github.com/unit8co/darts
    
  • PyPi (πŸ“₯ 86K / month Β· πŸ“¦ 10 Β· ⏱️ 03.10.2025):

    pip install u8darts
    
  • Conda (πŸ“₯ 94K Β· ⏱️ 05.10.2025):

    conda install -c conda-forge u8darts-all
    
  • Docker Hub (πŸ“₯ 2.1K Β· ⏱️ 03.10.2025):

    docker pull unit8/darts
    
</details> <details><summary><b><a href="https://github.com/sktime/pytorch-forecasting">pytorch-forecasting</a></b> (πŸ₯ˆ32 Β· ⭐ 4.6K) - Time series forecasting with PyTorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 79 Β· πŸ”€ 710 Β· πŸ“¦ 670 Β· πŸ“‹ 920 - 59% open Β· ⏱️ 19.10.2025):

    git clone https://github.com/jdb78/pytorch-forecasting
    
  • PyPi (πŸ“₯ 270K / month Β· πŸ“¦ 27 Β· ⏱️ 10.10.2025):

    pip install pytorch-forecasting
    
  • Conda (πŸ“₯ 87K Β· ⏱️ 05.07.2025):

    conda install -c conda-forge pytorch-forecasting
    
</details> <details><summary><b><a href="https://github.com/alkaline-ml/pmdarima">pmdarima</a></b> (πŸ₯ˆ32 Β· ⭐ 1.7K Β· πŸ’€) - A statistical library designed to fill the void in Pythons time.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 250 Β· πŸ“¦ 13K Β· πŸ“‹ 340 - 19% open Β· ⏱️ 07.11.2024):

    git clone https://github.com/alkaline-ml/pmdarima
    
  • PyPi (πŸ“₯ 7.5M / month Β· πŸ“¦ 150 Β· ⏱️ 23.10.2023):

    pip install pmdarima
    
  • Conda (πŸ“₯ 1.4M Β· ⏱️ 22.04.2025):

    conda install -c conda-forge pmdarima
    
</details> <details><summary><b><a href="https://github.com/blue-yonder/tsfresh">tsfresh</a></b> (πŸ₯ˆ31 Β· ⭐ 9K) - Automatic extraction of relevant features from time series:. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 1.3K Β· πŸ“¦ 21 Β· πŸ“‹ 550 - 12% open Β· ⏱️ 30.08.2025):

    git clone https://github.com/blue-yonder/tsfresh
    
  • PyPi (πŸ“₯ 340K / month Β· πŸ“¦ 120 Β· ⏱️ 30.08.2025):

    pip install tsfresh
    
  • Conda (πŸ“₯ 1.5M Β· ⏱️ 31.08.2025):

    conda install -c conda-forge tsfresh
    
</details> <details><summary><b><a href="https://github.com/stumpy-dev/stumpy">STUMPY</a></b> (πŸ₯ˆ30 Β· ⭐ 4K) - STUMPY is a powerful and scalable Python library for modern time series.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 340 Β· πŸ“¦ 1.6K Β· πŸ“‹ 540 - 13% open Β· ⏱️ 02.09.2025):

    git clone https://github.com/TDAmeritrade/stumpy
    
  • PyPi (πŸ“₯ 380K / month Β· πŸ“¦ 30 Β· ⏱️ 09.07.2024):

    pip install stumpy
    
  • Conda (πŸ“₯ 1.1M Β· ⏱️ 22.04.2025):

    conda install -c conda-forge stumpy
    
</details> <details><summary><b><a href="https://github.com/Nixtla/neuralforecast">NeuralForecast</a></b> (πŸ₯ˆ30 Β· ⭐ 3.8K) - Scalable and user friendly neural forecasting algorithms. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 55 Β· πŸ”€ 450 Β· πŸ“‹ 650 - 17% open Β· ⏱️ 01.10.2025):

    git clone https://github.com/Nixtla/neuralforecast
    
  • PyPi (πŸ“₯ 160K / month Β· πŸ“¦ 30 Β· ⏱️ 01.10.2025):

    pip install neuralforecast
    
  • Conda (πŸ“₯ 47K Β· ⏱️ 06.10.2025):

    conda install -c conda-forge neuralforecast
    
</details> <details><summary><b><a href="https://github.com/awslabs/gluonts">GluonTS</a></b> (πŸ₯ˆ29 Β· ⭐ 5K) - Probabilistic time series modeling in Python. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1X" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 790 Β· πŸ“‹ 970 - 34% open Β· ⏱️ 14.08.2025):

    git clone https://github.com/awslabs/gluon-ts
    
  • PyPi (πŸ“₯ 1.9M / month Β· πŸ“¦ 41 Β· ⏱️ 27.06.2025):

    pip install gluonts
    
  • Conda (πŸ“₯ 3.2K Β· ⏱️ 22.04.2025):

    conda install -c anaconda gluonts
    
</details> <details><summary><b><a href="https://github.com/python-streamz/streamz">Streamz</a></b> (πŸ₯‰28 Β· ⭐ 1.3K Β· πŸ’€) - Real-time stream processing for python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 49 Β· πŸ”€ 150 Β· πŸ“¦ 570 Β· πŸ“‹ 270 - 44% open Β· ⏱️ 22.11.2024):

    git clone https://github.com/python-streamz/streamz
    
  • PyPi (πŸ“₯ 26K / month Β· πŸ“¦ 57 Β· ⏱️ 27.07.2022):

    pip install streamz
    
  • Conda (πŸ“₯ 2.9M Β· ⏱️ 22.04.2025):

    conda install -c conda-forge streamz
    
</details> <details><summary><b><a href="https://github.com/johannfaouzi/pyts">pyts</a></b> (πŸ₯‰27 Β· ⭐ 1.9K) - A Python package for time series classification. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 180 Β· πŸ“¦ 900 Β· πŸ“‹ 88 - 59% open Β· ⏱️ 18.06.2025):

    git clone https://github.com/johannfaouzi/pyts
    
  • PyPi (πŸ“₯ 190K / month Β· πŸ“¦ 45 Β· ⏱️ 18.06.2023):

    pip install pyts
    
  • Conda (πŸ“₯ 35K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge pyts
    
</details> <details><summary><b><a href="https://github.com/fraunhoferportugal/tsfel">TSFEL</a></b> (πŸ₯‰26 Β· ⭐ 1.1K) - An intuitive library to extract features from time series. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 150 Β· πŸ“¦ 220 Β· πŸ“‹ 87 - 5% open Β· ⏱️ 20.08.2025):

    git clone https://github.com/fraunhoferportugal/tsfel
    
  • PyPi (πŸ“₯ 9.4K / month Β· πŸ“¦ 14 Β· ⏱️ 20.08.2025):

    pip install tsfel
    
</details> <details><summary><b><a href="https://github.com/linkedin/greykite">greykite</a></b> (πŸ₯‰22 Β· ⭐ 1.8K Β· πŸ’€) - A flexible, intuitive and fast forecasting library. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 10 Β· πŸ”€ 110 Β· πŸ“₯ 39 Β· πŸ“¦ 47 Β· πŸ“‹ 110 - 11% open Β· ⏱️ 20.02.2025):

    git clone https://github.com/linkedin/greykite
    
  • PyPi (πŸ“₯ 11K / month Β· ⏱️ 20.02.2025):

    pip install greykite
    
</details> <details><summary>Show 13 hidden projects...</summary>
  • <b><a href="https://github.com/ourownstory/neural_prophet">NeuralProphet</a></b> (πŸ₯‰26 Β· ⭐ 4.2K Β· πŸ’€) - NeuralProphet: A simple forecasting package. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/RJT1990/pyflux">PyFlux</a></b> (πŸ₯‰25 Β· ⭐ 2.1K Β· πŸ’€) - Open source time series library for Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/linkedin/luminol">luminol</a></b> (πŸ₯‰22 Β· ⭐ 1.2K Β· πŸ’€) - Anomaly Detection and Correlation library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/arundo/adtk">ADTK</a></b> (πŸ₯‰22 Β· ⭐ 1.2K Β· πŸ’€) - A Python toolkit for rule-based/unsupervised anomaly detection in.. <code><a href="http://bit.ly/3postzC">MPL-2.0</a></code>
  • <b><a href="https://github.com/dmbee/seglearn">seglearn</a></b> (πŸ₯‰21 Β· ⭐ 580 Β· πŸ’€) - Python module for machine learning time series:. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/wwrechard/pydlm">pydlm</a></b> (πŸ₯‰21 Β· ⭐ 480 Β· πŸ’€) - A python library for Bayesian time series modeling. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/X-DataInitiative/tick">tick</a></b> (πŸ₯‰20 Β· ⭐ 520 Β· πŸ’€) - Module for statistical learning, with a particular emphasis on time-.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/target/matrixprofile-ts">matrixprofile-ts</a></b> (πŸ₯‰19 Β· ⭐ 740 Β· πŸ’€) - A Python library for detecting patterns and anomalies.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/predict-idlab/tsflex">tsflex</a></b> (πŸ₯‰19 Β· ⭐ 430 Β· πŸ’€) - Flexible time series feature extraction & processing. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/AutoViML/Auto_TS">Auto TS</a></b> (πŸ₯‰17 Β· ⭐ 760 Β· πŸ’€) - Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/arundo/tsaug">tsaug</a></b> (πŸ₯‰15 Β· ⭐ 360 Β· πŸ’€) - A Python package for time series augmentation. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/firmai/atspy">atspy</a></b> (πŸ₯‰14 Β· ⭐ 520 Β· πŸ’€) - AtsPy: Automated Time Series Models in Python (by @firmai). <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/hsbc/tslumen">tslumen</a></b> (πŸ₯‰8 Β· ⭐ 71 Β· πŸ’€) - A library for Time Series EDA (exploratory data analysis). <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
</details> <br>

Medical Data

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic data, and other medical imaging formats.

<details><summary><b><a href="https://github.com/nilearn/nilearn">Nilearn</a></b> (πŸ₯‡38 Β· ⭐ 1.3K) - Machine learning for NeuroImaging in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 610 Β· πŸ“₯ 410 Β· πŸ“¦ 4.4K Β· πŸ“‹ 2.4K - 12% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/nilearn/nilearn
    
  • PyPi (πŸ“₯ 270K / month Β· πŸ“¦ 350 Β· ⏱️ 03.09.2025):

    pip install nilearn
    
  • Conda (πŸ“₯ 400K Β· ⏱️ 04.09.2025):

    conda install -c conda-forge nilearn
    
</details> <details><summary><b><a href="https://github.com/Project-MONAI/MONAI">MONAI</a></b> (πŸ₯‡37 Β· ⭐ 7K) - AI Toolkit for Healthcare Imaging. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 240 Β· πŸ”€ 1.3K Β· πŸ“¦ 4.5K Β· πŸ“‹ 3.3K - 14% open Β· ⏱️ 10.10.2025):

    git clone https://github.com/Project-MONAI/MONAI
    
  • PyPi (πŸ“₯ 320K / month Β· πŸ“¦ 200 Β· ⏱️ 22.09.2025):

    pip install monai
    
  • Conda (πŸ“₯ 60K Β· ⏱️ 22.09.2025):

    conda install -c conda-forge monai
    
</details> <details><summary><b><a href="https://github.com/mne-tools/mne-python">MNE</a></b> (πŸ₯‡37 Β· ⭐ 3.1K) - MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 410 Β· πŸ”€ 1.4K Β· πŸ“‹ 5.1K - 11% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/mne-tools/mne-python
    
  • PyPi (πŸ“₯ 280K / month Β· πŸ“¦ 530 Β· ⏱️ 14.10.2025):

    pip install mne
    
  • Conda (πŸ“₯ 620K Β· ⏱️ 14.10.2025):

    conda install -c conda-forge mne
    
</details> <details><summary><b><a href="https://github.com/hail-is/hail">Hail</a></b> (πŸ₯ˆ34 Β· ⭐ 1K) - Cloud-native genomic dataframes and batch computing. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 260 Β· πŸ“¦ 170 Β· πŸ“‹ 2.6K - 11% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/hail-is/hail
    
  • PyPi (πŸ“₯ 110K / month Β· πŸ“¦ 44 Β· ⏱️ 09.09.2025):

    pip install hail
    
</details> <details><summary><b><a href="https://github.com/nipy/nibabel">NiBabel</a></b> (πŸ₯ˆ34 Β· ⭐ 740) - Python package to access a cacophony of neuro-imaging file formats. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 260 Β· πŸ“¦ 30K Β· πŸ“‹ 550 - 23% open Β· ⏱️ 21.10.2025):

    git clone https://github.com/nipy/nibabel
    
  • PyPi (πŸ“₯ 910K / month Β· πŸ“¦ 1.2K Β· ⏱️ 23.10.2024):

    pip install nibabel
    
  • Conda (πŸ“₯ 1M Β· ⏱️ 22.04.2025):

    conda install -c conda-forge nibabel
    
</details> <details><summary><b><a href="https://github.com/nipy/nipype">NIPYPE</a></b> (πŸ₯ˆ33 Β· ⭐ 790) - Workflows and interfaces for neuroimaging packages. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 530 Β· πŸ“¦ 7.2K Β· πŸ“‹ 1.4K - 30% open Β· ⏱️ 28.04.2025):

    git clone https://github.com/nipy/nipype
    
  • PyPi (πŸ“₯ 360K / month Β· πŸ“¦ 150 Β· ⏱️ 19.03.2025):

    pip install nipype
    
  • Conda (πŸ“₯ 990K Β· ⏱️ 05.05.2025):

    conda install -c conda-forge nipype
    
</details> <details><summary><b><a href="https://github.com/CamDavidsonPilon/lifelines">Lifelines</a></b> (πŸ₯ˆ32 Β· ⭐ 2.5K Β· πŸ’€) - Survival analysis in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 560 Β· πŸ“¦ 4.2K Β· πŸ“‹ 980 - 27% open Β· ⏱️ 29.10.2024):

    git clone https://github.com/CamDavidsonPilon/lifelines
    
  • PyPi (πŸ“₯ 1.5M / month Β· πŸ“¦ 160 Β· ⏱️ 29.10.2024):

    pip install lifelines
    
  • Conda (πŸ“₯ 500K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge lifelines
    
</details> <details><summary><b><a href="https://github.com/google/deepvariant">DeepVariant</a></b> (πŸ₯‰27 Β· ⭐ 3.5K) - DeepVariant is an analysis pipeline that uses a deep neural.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 760 Β· πŸ“₯ 4.9K Β· πŸ“¦ 4 Β· πŸ“‹ 960 - 0% open Β· ⏱️ 10.09.2025):

    git clone https://github.com/google/deepvariant
    
  • Conda (πŸ“₯ 79K Β· ⏱️ 24.05.2025):

    conda install -c bioconda deepvariant
    
</details> <details><summary><b><a href="https://github.com/brainiak/brainiak">Brainiak</a></b> (πŸ₯‰19 Β· ⭐ 360 Β· πŸ’€) - Brain Imaging Analysis Kit. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 140 Β· πŸ“‹ 230 - 38% open Β· ⏱️ 06.01.2025):

    git clone https://github.com/brainiak/brainiak
    
  • PyPi (πŸ“₯ 1.3K / month Β· ⏱️ 07.01.2025):

    pip install brainiak
    
  • Docker Hub (πŸ“₯ 2K Β· ⭐ 1 Β· ⏱️ 07.01.2025):

    docker pull brainiak/brainiak
    
</details> <details><summary>Show 10 hidden projects...</summary>
  • <b><a href="https://github.com/dipy/dipy">DIPY</a></b> (πŸ₯ˆ31 Β· ⭐ 790) - DIPY is the paragon 3D/4D+ medical imaging library in Python... <code>❗Unlicensed</code>
  • <b><a href="https://github.com/NifTK/NiftyNet">NiftyNet</a></b> (πŸ₯‰24 Β· ⭐ 1.4K Β· πŸ’€) - [unmaintained] An open-source convolutional neural.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/nipy/nipy">NIPY</a></b> (πŸ₯‰24 Β· ⭐ 400 Β· πŸ’€) - Neuroimaging in Python FMRI analysis package. <code>❗Unlicensed</code>
  • <b><a href="https://github.com/loli/medpy">MedPy</a></b> (πŸ₯‰23 Β· ⭐ 610 Β· πŸ’€) - Medical image processing in Python. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code>
  • <b><a href="https://github.com/DLTK/DLTK">DLTK</a></b> (πŸ₯‰20 Β· ⭐ 1.4K Β· πŸ’€) - Deep Learning Toolkit for Medical Image Analysis. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/projectglow/glow">Glow</a></b> (πŸ₯‰19 Β· ⭐ 290 Β· πŸ’€) - An open-source toolkit for large-scale genomic analysis. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/perone/medicaltorch">MedicalTorch</a></b> (πŸ₯‰17 Β· ⭐ 870 Β· πŸ’€) - A medical imaging framework for Pytorch. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/MIC-DKFZ/medicaldetectiontoolkit">Medical Detection Toolkit</a></b> (πŸ₯‰14 Β· ⭐ 1.3K Β· πŸ’€) - The Medical Detection Toolkit contains 2D + 3D.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/QTIM-Lab/DeepNeuro">DeepNeuro</a></b> (πŸ₯‰14 Β· ⭐ 130 Β· πŸ’€) - A deep learning python package for neuroimaging data. Made by:. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/Tencent/MedicalNet">MedicalNet</a></b> (πŸ₯‰12 Β· ⭐ 2.1K Β· πŸ’€) - Many studies have shown that the performance on deep learning is.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
</details> <br>

Tabular Data

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries for processing tabular and structured data.

<details><summary><b><a href="https://github.com/skrub-data/skrub">skrub</a></b> (πŸ₯‡30 Β· ⭐ 1.5K) - Machine learning with dataframes. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 170 Β· πŸ“¦ 100 Β· πŸ“‹ 580 - 21% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/skrub-data/skrub
    
  • PyPi (πŸ“₯ 45K / month Β· πŸ“¦ 20 Β· ⏱️ 25.09.2025):

    pip install skrub
    
</details> <details><summary><b><a href="https://github.com/manujosephv/pytorch_tabular">pytorch_tabular</a></b> (πŸ₯ˆ23 Β· ⭐ 1.6K) - A standard framework for modelling Deep Learning Models.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 160 Β· πŸ“₯ 64 Β· πŸ“‹ 180 - 5% open Β· ⏱️ 19.04.2025):

    git clone https://github.com/manujosephv/pytorch_tabular
    
  • PyPi (πŸ“₯ 5.5K / month Β· πŸ“¦ 9 Β· ⏱️ 28.11.2024):

    pip install pytorch_tabular
    
</details> <details><summary><b><a href="https://github.com/upgini/upgini">upgini</a></b> (πŸ₯ˆ21 Β· ⭐ 350) - Data search & enrichment library for Machine Learning Easily find and add.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 25 Β· πŸ“¦ 9 Β· ⏱️ 28.10.2025):

    git clone https://github.com/upgini/upgini
    
  • PyPi (πŸ“₯ 5.9K / month Β· ⏱️ 28.10.2025):

    pip install upgini
    
</details> <details><summary>Show 3 hidden projects...</summary>
  • <b><a href="https://github.com/AnotherSamWilson/miceforest">miceforest</a></b> (πŸ₯ˆ21 Β· ⭐ 390) - Multiple Imputation with LightGBM in Python. <code>❗Unlicensed</code>
  • <b><a href="https://github.com/carefree0910/carefree-learn">carefree-learn</a></b> (πŸ₯‰18 Β· ⭐ 410 Β· πŸ’€) - Deep Learning PyTorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/firmai/deltapy">deltapy</a></b> (πŸ₯‰13 Β· ⭐ 550 Β· πŸ’€) - DeltaPy - Tabular Data Augmentation (by @firmai). <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
</details> <br>

Optical Character Recognition

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries for optical character recognition (OCR) and text extraction from images or videos.

<details><summary><b><a href="https://github.com/PaddlePaddle/PaddleOCR">PaddleOCR</a></b> (πŸ₯‡44 Β· ⭐ 62K) - Turn any PDF or image document into structured data for your.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1M" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 9.2K Β· πŸ“₯ 2M Β· πŸ“¦ 6.2K Β· πŸ“‹ 10K - 1% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/PaddlePaddle/PaddleOCR
    
  • PyPi (πŸ“₯ 750K / month Β· πŸ“¦ 210 Β· ⏱️ 29.10.2025):

    pip install paddleocr
    
</details> <details><summary><b><a href="https://github.com/ocrmypdf/OCRmyPDF">OCRmyPDF</a></b> (πŸ₯‡37 Β· ⭐ 32K) - OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them.. <code><a href="http://bit.ly/3postzC">MPL-2.0</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 2.2K Β· πŸ“₯ 15K Β· πŸ“¦ 1.4K Β· πŸ“‹ 1.3K - 11% open Β· ⏱️ 25.10.2025):

    git clone https://github.com/ocrmypdf/OCRmyPDF
    
  • PyPi (πŸ“₯ 400K / month Β· πŸ“¦ 58 Β· ⏱️ 16.10.2025):

    pip install ocrmypdf
    
  • Conda (πŸ“₯ 110K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge ocrmypdf
    
</details> <details><summary><b><a href="https://github.com/madmaze/pytesseract">Tesseract</a></b> (πŸ₯ˆ32 Β· ⭐ 6.2K Β· πŸ’€) - Python-tesseract is an optical character recognition (OCR).. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 50 Β· πŸ”€ 730 Β· πŸ“‹ 370 - 3% open Β· ⏱️ 17.02.2025):

    git clone https://github.com/madmaze/pytesseract
    
  • PyPi (πŸ“₯ 5.6M / month Β· πŸ“¦ 970 Β· ⏱️ 16.08.2024):

    pip install pytesseract
    
  • Conda (πŸ“₯ 690K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge pytesseract
    
</details> <details><summary><b><a href="https://github.com/sirfz/tesserocr">tesserocr</a></b> (πŸ₯ˆ32 Β· ⭐ 2.1K) - A Python wrapper for the tesseract-ocr API. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 260 Β· πŸ“₯ 1.2K Β· πŸ“¦ 1.3K Β· πŸ“‹ 290 - 14% open Β· ⏱️ 10.10.2025):

    git clone https://github.com/sirfz/tesserocr
    
  • PyPi (πŸ“₯ 210K / month Β· πŸ“¦ 56 Β· ⏱️ 10.10.2025):

    pip install tesserocr
    
  • Conda (πŸ“₯ 290K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge tesserocr
    
</details> <details><summary><b><a href="https://github.com/open-mmlab/mmocr">MMOCR</a></b> (πŸ₯‰27 Β· ⭐ 4.7K Β· πŸ’€) - OpenMMLab Text Detection, Recognition and Understanding Toolbox. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 770 Β· πŸ“¦ 240 Β· πŸ“‹ 930 - 20% open Β· ⏱️ 27.11.2024):

    git clone https://github.com/open-mmlab/mmocr
    
  • PyPi (πŸ“₯ 6K / month Β· πŸ“¦ 4 Β· ⏱️ 05.05.2022):

    pip install mmocr
    
</details> <details><summary><b><a href="https://github.com/faustomorales/keras-ocr">keras-ocr</a></b> (πŸ₯‰25 Β· ⭐ 1.5K) - A packaged and flexible version of the CRAFT text detector and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 340 Β· πŸ“₯ 2.1M Β· πŸ“¦ 720 Β· πŸ“‹ 220 - 46% open Β· ⏱️ 22.09.2025):

    git clone https://github.com/faustomorales/keras-ocr
    
  • PyPi (πŸ“₯ 18K / month Β· πŸ“¦ 8 Β· ⏱️ 06.11.2023):

    pip install keras-ocr
    
  • Conda (πŸ“₯ 450 Β· ⏱️ 22.04.2025):

    conda install -c anaconda keras-ocr
    
</details> <details><summary>Show 6 hidden projects...</summary>
  • <b><a href="https://github.com/JaidedAI/EasyOCR">EasyOCR</a></b> (πŸ₯ˆ34 Β· ⭐ 28K Β· πŸ’€) - Ready-to-use OCR with 80+ supported languages and all popular.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/Calamari-OCR/calamari">calamari</a></b> (πŸ₯‰22 Β· ⭐ 1.2K) - Line based ATR Engine based on OCRopy. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code>
  • <b><a href="https://github.com/WZBSocialScienceCenter/pdftabextract">pdftabextract</a></b> (πŸ₯‰21 Β· ⭐ 2.2K Β· πŸ’€) - A set of tools for extracting tables from PDF files.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/emedvedev/attention-ocr">attention-ocr</a></b> (πŸ₯‰21 Β· ⭐ 1.1K Β· πŸ’€) - A Tensorflow model for text recognition (CNN + seq2seq.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/jlsutherland/doc2text">doc2text</a></b> (πŸ₯‰20 Β· ⭐ 1.3K Β· πŸ’€) - Detect text blocks and OCR poorly scanned PDFs in bulk. Python.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/aashrafh/Mozart">Mozart</a></b> (πŸ₯‰10 Β· ⭐ 690 Β· πŸ’€) - An optical music recognition (OMR) system. Converts sheet.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
</details> <br>

Data Containers & Structures

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

General-purpose data containers & structures as well as utilities & extensions for pandas.

πŸ”—Β <b><a href="https://github.com/ml-tooling/best-of-python#data-containers--dataframes">best-of-python - Data Containers</a></b> ( ⭐ 4.2K) - Collection of data-container, dataframe, and pandas-..

<br>

Data Loading & Extraction

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries for loading, collecting, and extracting data from a variety of data sources and formats.

πŸ”—Β <b><a href="https://github.com/ml-tooling/best-of-python#data-loading--extraction">best-of-python - Data Extraction</a></b> ( ⭐ 4.2K) - Collection of data-loading and -extraction libraries.

<br>

Web Scraping & Crawling

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries for web scraping, crawling, downloading, and mining as well as libraries.

πŸ”—Β <b><a href="https://github.com/ml-tooling/best-of-web-python#web-scraping--crawling">best-of-web-python - Web Scraping</a></b> ( ⭐ 2.6K) - Collection of web-scraping and crawling libraries.

<br>

Data Pipelines & Streaming

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries for data batch- and stream-processing, workflow automation, job scheduling, and other data pipeline tasks.

πŸ”—Β <b><a href="https://github.com/ml-tooling/best-of-python#data-pipelines--streaming">best-of-python - Data Pipelines</a></b> ( ⭐ 4.2K) - Libraries for data batch- and stream-processing,..

<details><summary>Show 1 hidden projects...</summary>
  • <b><a href="https://github.com/clugen/pyclugen">pyclugen</a></b> (πŸ₯‡10 Β· ⭐ 10) - Multidimensional cluster generation in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
</details> <br>

Distributed Machine Learning

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries that provide capabilities to distribute and parallelize machine learning tasks across large-scale compute infrastructure.

<details><summary><b><a href="https://github.com/ray-project/ray">Ray</a></b> (πŸ₯‡48 Β· ⭐ 40K) - Ray is an AI compute engine. Ray consists of a core distributed runtime.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 1.4K Β· πŸ”€ 6.8K Β· πŸ“₯ 270 Β· πŸ“¦ 27K Β· πŸ“‹ 22K - 14% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/ray-project/ray
    
  • PyPi (πŸ“₯ 30M / month Β· πŸ“¦ 1.1K Β· ⏱️ 29.10.2025):

    pip install ray
    
  • Conda (πŸ“₯ 920K Β· ⏱️ 22.10.2025):

    conda install -c conda-forge ray-tune
    
</details> <details><summary><b><a href="https://github.com/dask/dask">dask</a></b> (πŸ₯‡45 Β· ⭐ 14K Β· πŸ“ˆ) - Parallel computing with task scheduling. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 630 Β· πŸ”€ 1.8K Β· πŸ“¦ 77K Β· πŸ“‹ 5.6K - 21% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/dask/dask
    
  • PyPi (πŸ“₯ 20M / month Β· πŸ“¦ 3.2K Β· ⏱️ 14.10.2025):

    pip install dask
    
  • Conda (πŸ“₯ 14M Β· ⏱️ 14.10.2025):

    conda install -c conda-forge dask
    
</details> <details><summary><b><a href="https://github.com/deepspeedai/DeepSpeed">DeepSpeed</a></b> (πŸ₯‡41 Β· ⭐ 41K) - DeepSpeed is a deep learning optimization library that makes.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 420 Β· πŸ”€ 4.6K Β· πŸ“¦ 15K Β· πŸ“‹ 3.2K - 34% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/microsoft/DeepSpeed
    
  • PyPi (πŸ“₯ 990K / month Β· πŸ“¦ 350 Β· ⏱️ 23.10.2025):

    pip install deepspeed
    
  • Docker Hub (πŸ“₯ 24K Β· ⭐ 4 Β· ⏱️ 02.09.2022):

    docker pull deepspeed/deepspeed
    
</details> <details><summary><b><a href="https://github.com/dask/distributed">dask.distributed</a></b> (πŸ₯‡39 Β· ⭐ 1.7K) - A distributed task scheduler for Dask. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 340 Β· πŸ”€ 740 Β· πŸ“¦ 42K Β· πŸ“‹ 3.9K - 37% open Β· ⏱️ 28.10.2025):

    git clone https://github.com/dask/distributed
    
  • PyPi (πŸ“₯ 5.4M / month Β· πŸ“¦ 1K Β· ⏱️ 14.10.2025):

    pip install distributed
    
  • Conda (πŸ“₯ 20M Β· ⏱️ 14.10.2025):

    conda install -c conda-forge distributed
    
</details> <details><summary><b><a href="https://github.com/horovod/horovod">horovod</a></b> (πŸ₯ˆ36 Β· ⭐ 15K) - Distributed training framework for TensorFlow, Keras, PyTorch, and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 2.3K Β· πŸ“¦ 1.4K Β· πŸ“‹ 2.3K - 17% open Β· ⏱️ 28.10.2025):

    git clone https://github.com/horovod/horovod
    
  • PyPi (πŸ“₯ 78K / month Β· πŸ“¦ 34 Β· ⏱️ 12.06.2023):

    pip install horovod
    
</details> <details><summary><b><a href="https://github.com/Lightning-AI/torchmetrics">metrics</a></b> (πŸ₯ˆ36 Β· ⭐ 2.3K) - Machine learning metrics for distributed, scalable PyTorch.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 280 Β· πŸ”€ 460 Β· πŸ“₯ 6.9K Β· πŸ“¦ 45K Β· πŸ“‹ 990 - 8% open Β· ⏱️ 27.10.2025):

    git clone https://github.com/Lightning-AI/metrics
    
  • PyPi (πŸ“₯ 4.6K / month Β· πŸ“¦ 4 Β· ⏱️ 26.02.2025):

    pip install metrics
    
  • Conda (πŸ“₯ 2.2M Β· ⏱️ 03.09.2025):

    conda install -c conda-forge torchmetrics
    
</details> <details><summary><b><a href="https://github.com/h2oai/h2o-3">H2O-3</a></b> (πŸ₯ˆ34 Β· ⭐ 7.3K) - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 280 Β· πŸ”€ 2K Β· πŸ“¦ 99 Β· πŸ“‹ 9.6K - 30% open Β· ⏱️ 21.10.2025):

    git clone https://github.com/h2oai/h2o-3
    
  • PyPi (πŸ“₯ 180K / month Β· πŸ“¦ 68 Β· ⏱️ 08.10.2025):

    pip install h2o
    
</details> <details><summary><b><a href="https://github.com/hpcaitech/ColossalAI">ColossalAI</a></b> (πŸ₯ˆ33 Β· ⭐ 41K) - Making large AI models cheaper, faster and more accessible. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 200 Β· πŸ”€ 4.5K Β· πŸ“¦ 530 Β· πŸ“‹ 1.8K - 26% open Β· ⏱️ 26.09.2025):

    git clone https://github.com/hpcaitech/colossalai
    
</details> <details><summary><b><a href="https://github.com/mpi4py/mpi4py">mpi4py</a></b> (πŸ₯ˆ33 Β· ⭐ 880) - Python bindings for MPI. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 130 Β· πŸ“₯ 39K Β· πŸ“¦ 12K Β· πŸ“‹ 230 - 2% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/mpi4py/mpi4py
    
  • PyPi (πŸ“₯ 980K / month Β· πŸ“¦ 1K Β· ⏱️ 10.10.2025):

    pip install mpi4py
    
  • Conda (πŸ“₯ 4.5M Β· ⏱️ 14.10.2025):

    conda install -c conda-forge mpi4py
    
</details> <details><summary><b><a href="https://github.com/facebookresearch/fairscale">FairScale</a></b> (πŸ₯ˆ31 Β· ⭐ 3.4K) - PyTorch extensions for high performance and large scale training. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 77 Β· πŸ”€ 290 Β· πŸ“¦ 9K Β· πŸ“‹ 390 - 26% open Β· ⏱️ 26.04.2025):

    git clone https://github.com/facebookresearch/fairscale
    
  • PyPi (πŸ“₯ 530K / month Β· πŸ“¦ 150 Β· ⏱️ 11.12.2022):

    pip install fairscale
    
  • Conda (πŸ“₯ 530K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge fairscale
    
</details> <details><summary><b><a href="https://github.com/facebookincubator/submitit">Submit it</a></b> (πŸ₯ˆ31 Β· ⭐ 1.5K) - Python 3.8+ toolbox for submitting jobs to Slurm. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 26 Β· πŸ”€ 140 Β· πŸ“¦ 4.7K Β· πŸ“‹ 130 - 38% open Β· ⏱️ 21.05.2025):

    git clone https://github.com/facebookincubator/submitit
    
  • PyPi (πŸ“₯ 840K / month Β· πŸ“¦ 74 Β· ⏱️ 21.05.2025):

    pip install submitit
    
  • Conda (πŸ“₯ 65K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge submitit
    
</details> <details><summary><b><a href="https://github.com/intel/ipex-llm">BigDL</a></b> (πŸ₯ˆ30 Β· ⭐ 8.4K) - Accelerate local LLM inference and finetuning (LLaMA, Mistral,.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 1.4K Β· πŸ“₯ 710 Β· πŸ“‹ 3K - 40% open Β· ⏱️ 14.10.2025):

    git clone https://github.com/intel-analytics/BigDL
    
  • PyPi (πŸ“₯ 15K / month Β· πŸ“¦ 2 Β· ⏱️ 24.03.2024):

    pip install bigdl
    
  • Maven (πŸ“¦ 5 Β· ⏱️ 20.04.2021):

    <dependency>
    	<groupId>com.intel.analytics.bigdl</groupId>
    	<artifactId>bigdl-SPARK_2.4</artifactId>
    	<version>[VERSION]</version>
    </dependency>
    
</details> <details><summary><b><a href="https://github.com/microsoft/SynapseML">SynapseML</a></b> (πŸ₯ˆ30 Β· ⭐ 5.2K) - Simple and Distributed Machine Learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 850 Β· πŸ“‹ 820 - 49% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/microsoft/SynapseML
    
  • PyPi (πŸ“₯ 1.6M / month Β· πŸ“¦ 7 Β· ⏱️ 03.10.2025):

    pip install synapseml
    
</details> <details><summary><b><a href="https://github.com/uber/petastorm">petastorm</a></b> (πŸ₯ˆ29 Β· ⭐ 1.9K) - Petastorm library enables single machine or distributed training.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 52 Β· πŸ”€ 280 Β· πŸ“₯ 580 Β· πŸ“¦ 390 Β· πŸ“‹ 330 - 54% open Β· ⏱️ 15.09.2025):

    git clone https://github.com/uber/petastorm
    
  • PyPi (πŸ“₯ 270K / month Β· πŸ“¦ 15 Β· ⏱️ 11.08.2025):

    pip install petastorm
    
</details> <details><summary><b><a href="https://github.com/dask/dask-ml">dask-ml</a></b> (πŸ₯‰28 Β· ⭐ 940) - Scalable Machine Learning with Dask. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 260 Β· πŸ“¦ 1.3K Β· πŸ“‹ 550 - 51% open Β· ⏱️ 27.09.2025):

    git clone https://github.com/dask/dask-ml
    
  • PyPi (πŸ“₯ 120K / month Β· πŸ“¦ 100 Β· ⏱️ 08.02.2025):

    pip install dask-ml
    
  • Conda (πŸ“₯ 1.1M Β· ⏱️ 22.04.2025):

    conda install -c conda-forge dask-ml
    
</details> <details><summary><b><a href="https://github.com/learning-at-home/hivemind">Hivemind</a></b> (πŸ₯‰26 Β· ⭐ 2.3K) - Decentralized deep learning in PyTorch. Built to train models on.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 190 Β· πŸ“¦ 130 Β· πŸ“‹ 190 - 43% open Β· ⏱️ 12.10.2025):

    git clone https://github.com/learning-at-home/hivemind
    
  • PyPi (πŸ“₯ 43K / month Β· πŸ“¦ 12 Β· ⏱️ 20.04.2025):

    pip install hivemind
    
</details> <details><summary><b><a href="https://github.com/microsoft/SynapseML">MMLSpark</a></b> (πŸ₯‰23 Β· ⭐ 5.2K) - Simple and Distributed Machine Learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 850 Β· πŸ“‹ 820 - 49% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/microsoft/SynapseML
    
  • PyPi (⏱️ 18.03.2020):

    pip install mmlspark
    
</details> <details><summary><b><a href="https://github.com/apache/singa">Apache Singa</a></b> (πŸ₯‰23 Β· ⭐ 3.6K Β· πŸ’€) - a distributed deep learning platform. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 98 Β· πŸ”€ 1.3K Β· πŸ“¦ 6 Β· πŸ“‹ 140 - 35% open Β· ⏱️ 26.03.2025):

    git clone https://github.com/apache/singa
    
  • Conda (πŸ“₯ 1.2K Β· ⏱️ 25.03.2025):

    conda install -c nusdbsystem singa
    
  • Docker Hub (πŸ“₯ 9.9K Β· ⭐ 3 Β· ⏱️ 31.05.2022):

    docker pull apache/singa
    
</details> <details><summary><b><a href="https://github.com/intel/analytics-zoo">analytics-zoo</a></b> (πŸ₯‰22 Β· ⭐ 2.6K) - Distributed Tensorflow, Keras and PyTorch on Apache.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 730 Β· πŸ“‹ 1.3K - 32% open Β· ⏱️ 09.10.2025):

    git clone https://github.com/intel-analytics/analytics-zoo
    
  • PyPi (πŸ“₯ 600 / month Β· πŸ“¦ 1 Β· ⏱️ 22.08.2022):

    pip install analytics-zoo
    
</details> <details><summary>Show 17 hidden projects...</summary>
  • <b><a href="https://github.com/DEAP/deap">DEAP</a></b> (πŸ₯ˆ34 Β· ⭐ 6.2K) - Distributed Evolutionary Algorithms in Python. <code><a href="http://bit.ly/37RvQcA">❗️LGPL-3.0</a></code>
  • <b><a href="https://github.com/ipython/ipyparallel">ipyparallel</a></b> (πŸ₯ˆ29 Β· ⭐ 2.6K) - IPython Parallel: Interactive Parallel Computing in.. <code>❗Unlicensed</code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/yahoo/TensorFlowOnSpark">TensorFlowOnSpark</a></b> (πŸ₯‰25 Β· ⭐ 3.9K Β· πŸ’€) - TensorFlowOnSpark brings TensorFlow programs to.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/maxpumperla/elephas">Elephas</a></b> (πŸ₯‰24 Β· ⭐ 1.6K Β· πŸ’€) - Distributed Deep learning with Keras & Spark. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code>keras</code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/tensorflow/mesh">Mesh</a></b> (πŸ₯‰23 Β· ⭐ 1.6K Β· πŸ’€) - Mesh TensorFlow: Model Parallelism Made Easier. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/bytedance/byteps">BytePS</a></b> (πŸ₯‰21 Β· ⭐ 3.7K Β· πŸ’€) - A high performance and generic framework for distributed DNN.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/peterwittek/somoclu">somoclu</a></b> (πŸ₯‰21 Β· ⭐ 280 Β· πŸ’€) - Massively parallel self-organizing maps: accelerate training on.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/databricks/tensorframes">TensorFrames</a></b> (πŸ₯‰19 Β· ⭐ 750 Β· πŸ’€) - [DEPRECATED] Tensorflow wrapper for DataFrames on.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/Ibotta/sk-dist">sk-dist</a></b> (πŸ₯‰19 Β· ⭐ 290 Β· πŸ’€) - Distributed scikit-learn meta-estimators in PySpark. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/kingoflolz/mesh-transformer-jax">mesh-transformer-jax</a></b> (πŸ₯‰18 Β· ⭐ 6.4K Β· πŸ’€) - Model parallel transformers in JAX and Haiku. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/google-deepmind/launchpad">launchpad</a></b> (πŸ₯‰18 Β· ⭐ 330 Β· πŸ’€) - Launchpad is a library that simplifies writing.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/uber/fiber">Fiber</a></b> (πŸ₯‰17 Β· ⭐ 1K Β· πŸ’€) - Distributed Computing for AI Made Simple. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/Bluefog-Lib/bluefog">bluefog</a></b> (πŸ₯‰17 Β· ⭐ 290 Β· πŸ’€) - Distributed and decentralized training framework for PyTorch.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/tunib-ai/parallelformers">parallelformers</a></b> (πŸ₯‰16 Β· ⭐ 790 Β· πŸ’€) - Parallelformers: An Efficient Model Parallelization.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/ml-tooling/lazycluster">LazyCluster</a></b> (πŸ₯‰13 Β· ⭐ 49 Β· πŸ’€) - Distributed machine learning made simple. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/petuum/autodist">autodist</a></b> (πŸ₯‰12 Β· ⭐ 130 Β· πŸ’€) - Simple Distributed Deep Learning on TensorFlow. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/facebookresearch/moolib">moolib</a></b> (πŸ₯‰11 Β· ⭐ 370 Β· πŸ’€) - A library for distributed ML training with PyTorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
</details> <br>

Hyperparameter Optimization & AutoML

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries for hyperparameter optimization, automl and neural architecture search.

<details><summary><b><a href="https://github.com/optuna/optuna">Optuna</a></b> (πŸ₯‡44 Β· ⭐ 13K) - A hyperparameter optimization framework. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 1.2K Β· πŸ“¦ 30K Β· πŸ“‹ 1.8K - 3% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/optuna/optuna
    
  • PyPi (πŸ“₯ 7.6M / month Β· πŸ“¦ 1.5K Β· ⏱️ 18.08.2025):

    pip install optuna
    
  • Conda (πŸ“₯ 3.4M Β· ⏱️ 19.08.2025):

    conda install -c conda-forge optuna
    
</details> <details><summary><b><a href="https://github.com/facebook/Ax">Ax</a></b> (πŸ₯‡36 Β· ⭐ 2.6K) - Adaptive Experimentation Platform. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 200 Β· πŸ”€ 350 Β· πŸ“¦ 1.2K Β· πŸ“‹ 930 - 12% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/facebook/Ax
    
  • PyPi (πŸ“₯ 240K / month Β· πŸ“¦ 71 Β· ⏱️ 09.09.2025):

    pip install ax-platform
    
  • Conda (πŸ“₯ 49K Β· ⏱️ 10.09.2025):

    conda install -c conda-forge ax-platform
    
</details> <details><summary><b><a href="https://github.com/autogluon/autogluon">AutoGluon</a></b> (πŸ₯‡35 Β· ⭐ 9.6K) - Fast and Accurate ML in 3 Lines of Code. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.1K Β· πŸ“¦ 1.2K Β· πŸ“‹ 1.8K - 24% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/autogluon/autogluon
    
  • PyPi (πŸ“₯ 260K / month Β· πŸ“¦ 38 Β· ⏱️ 23.10.2025):

    pip install autogluon
    
  • Conda (πŸ“₯ 45K Β· ⏱️ 30.07.2025):

    conda install -c conda-forge autogluon
    
  • Docker Hub (πŸ“₯ 20K Β· ⭐ 19 Β· ⏱️ 16.06.2025):

    docker pull autogluon/autogluon
    
</details> <details><summary><b><a href="https://github.com/meta-pytorch/botorch">BoTorch</a></b> (πŸ₯‡35 Β· ⭐ 3.4K) - Bayesian optimization in PyTorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 450 Β· πŸ“¦ 1.8K Β· πŸ“‹ 600 - 10% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/pytorch/botorch
    
  • PyPi (πŸ“₯ 480K / month Β· πŸ“¦ 140 Β· ⏱️ 23.10.2025):

    pip install botorch
    
  • Conda (πŸ“₯ 180K Β· ⏱️ 24.10.2025):

    conda install -c conda-forge botorch
    
</details> <details><summary><b><a href="https://github.com/bayesian-optimization/BayesianOptimization">Bayesian Optimization</a></b> (πŸ₯‡34 Β· ⭐ 8.4K) - A Python implementation of global optimization with.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 52 Β· πŸ”€ 1.6K Β· πŸ“₯ 180 Β· πŸ“¦ 4.1K Β· πŸ“‹ 390 - 1% open Β· ⏱️ 09.09.2025):

    git clone https://github.com/fmfn/BayesianOptimization
    
  • PyPi (πŸ“₯ 510K / month Β· πŸ“¦ 190 Β· ⏱️ 24.07.2025):

    pip install bayesian-optimization
    
</details> <details><summary><b><a href="https://github.com/hyperopt/hyperopt">Hyperopt</a></b> (πŸ₯‡34 Β· ⭐ 7.5K Β· πŸ’€) - Distributed Asynchronous Hyperparameter Optimization in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 1.1K Β· πŸ“¦ 22K Β· πŸ“‹ 800 - 17% open Β· ⏱️ 27.12.2024):

    git clone https://github.com/hyperopt/hyperopt
    
  • PyPi (πŸ“₯ 2.7M / month Β· πŸ“¦ 450 Β· ⏱️ 17.11.2021):

    pip install hyperopt
    
  • Conda (πŸ“₯ 860K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge hyperopt
    
</details> <details><summary><b><a href="https://github.com/keras-team/autokeras">AutoKeras</a></b> (πŸ₯ˆ32 Β· ⭐ 9.3K Β· πŸ’€) - AutoML library for deep learning. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 1.4K Β· πŸ“₯ 21K Β· πŸ“¦ 890 Β· πŸ“‹ 910 - 16% open Β· ⏱️ 16.12.2024):

    git clone https://github.com/keras-team/autokeras
    
  • PyPi (πŸ“₯ 15K / month Β· πŸ“¦ 13 Β· ⏱️ 20.03.2024):

    pip install autokeras
    
</details> <details><summary><b><a href="https://github.com/alteryx/featuretools">featuretools</a></b> (πŸ₯ˆ32 Β· ⭐ 7.6K Β· πŸ’€) - An open source python library for automated feature.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 75 Β· πŸ”€ 900 Β· πŸ“¦ 2.1K Β· πŸ“‹ 1K - 15% open Β· ⏱️ 13.11.2024):

    git clone https://github.com/alteryx/featuretools
    
  • PyPi (πŸ“₯ 100K / month Β· πŸ“¦ 74 Β· ⏱️ 14.05.2024):

    pip install featuretools
    
  • Conda (πŸ“₯ 270K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge featuretools
    
</details> <details><summary><b><a href="https://github.com/facebookresearch/nevergrad">nevergrad</a></b> (πŸ₯ˆ30 Β· ⭐ 4.1K) - A Python toolbox for performing gradient-free optimization. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 58 Β· πŸ”€ 360 Β· πŸ“¦ 1.2K Β· πŸ“‹ 310 - 40% open Β· ⏱️ 23.04.2025):

    git clone https://github.com/facebookresearch/nevergrad
    
  • PyPi (πŸ“₯ 150K / month Β· πŸ“¦ 72 Β· ⏱️ 23.04.2025):

    pip install nevergrad
    
  • Conda (πŸ“₯ 67K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge nevergrad
    
</details> <details><summary><b><a href="https://github.com/shankarpandala/lazypredict">lazypredict</a></b> (πŸ₯ˆ28 Β· ⭐ 3.2K) - Lazy Predict help build a lot of basic models without much code.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 360 Β· πŸ“¦ 1.4K Β· πŸ“‹ 160 - 64% open Β· ⏱️ 17.10.2025):

    git clone https://github.com/shankarpandala/lazypredict
    
  • PyPi (πŸ“₯ 31K / month Β· πŸ“¦ 8 Β· ⏱️ 05.04.2025):

    pip install lazypredict
    
  • Conda (πŸ“₯ 6.6K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge lazypredict
    
</details> <details><summary><b><a href="https://github.com/mljar/mljar-supervised">mljar-supervised</a></b> (πŸ₯ˆ28 Β· ⭐ 3.2K) - Python package for AutoML on Tabular Data with Feature.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 420 Β· πŸ“¦ 170 Β· πŸ“‹ 680 - 21% open Β· ⏱️ 07.07.2025):

    git clone https://github.com/mljar/mljar-supervised
    
  • PyPi (πŸ“₯ 8.7K / month Β· πŸ“¦ 6 Β· ⏱️ 07.07.2025):

    pip install mljar-supervised
    
  • Conda (πŸ“₯ 52K Β· ⏱️ 08.07.2025):

    conda install -c conda-forge mljar-supervised
    
</details> <details><summary><b><a href="https://github.com/SimonBlanke/Hyperactive">Hyperactive</a></b> (πŸ₯ˆ24 Β· ⭐ 530) - An optimization and data collection toolbox for convenient and fast.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 51 Β· πŸ“₯ 340 Β· πŸ“¦ 40 Β· πŸ“‹ 120 - 28% open Β· ⏱️ 25.10.2025):

    git clone https://github.com/SimonBlanke/Hyperactive
    
  • PyPi (πŸ“₯ 4K / month Β· πŸ“¦ 13 Β· ⏱️ 20.09.2025):

    pip install hyperactive
    
</details> <details><summary><b><a href="https://github.com/aimclub/FEDOT">FEDOT</a></b> (πŸ₯‰23 Β· ⭐ 700) - Automated modeling and machine learning framework FEDOT. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 89 Β· πŸ“¦ 65 Β· πŸ“‹ 570 - 11% open Β· ⏱️ 14.10.2025):

    git clone https://github.com/nccr-itmo/FEDOT
    
  • PyPi (πŸ“₯ 1.8K / month Β· πŸ“¦ 7 Β· ⏱️ 10.03.2025):

    pip install fedot
    
</details> <details><summary><b><a href="https://github.com/ScottfreeLLC/AlphaPy">AlphaPy</a></b> (πŸ₯‰21 Β· ⭐ 1.6K) - Python AutoML for Trading Systems and Sports Betting. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 5 Β· πŸ”€ 250 Β· πŸ“¦ 10 Β· πŸ“‹ 45 - 35% open Β· ⏱️ 24.08.2025):

    git clone https://github.com/ScottfreeLLC/AlphaPy
    
  • PyPi (πŸ“₯ 320 / month Β· ⏱️ 29.08.2020):

    pip install alphapy
    
</details> <details><summary><b><a href="https://github.com/AutoViML/Auto_ViML">Auto ViML</a></b> (πŸ₯‰20 Β· ⭐ 540 Β· πŸ’€) - Automatically Build Multiple ML Models with a Single Line of.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 100 Β· πŸ“¦ 28 Β· ⏱️ 30.01.2025):

    git clone https://github.com/AutoViML/Auto_ViML
    
  • PyPi (πŸ“₯ 2.6K / month Β· πŸ“¦ 3 Β· ⏱️ 30.01.2025):

    pip install autoviml
    
</details> <details><summary><b><a href="https://github.com/AutoViML/featurewiz">featurewiz</a></b> (πŸ₯‰18 Β· ⭐ 670 Β· πŸ’€) - Use advanced feature engineering strategies and select best.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 98 Β· πŸ“‹ 110 - 0% open Β· ⏱️ 19.02.2025):

    git clone https://github.com/AutoViML/featurewiz
    
  • PyPi (πŸ“₯ 4.6K / month Β· πŸ“¦ 4 Β· ⏱️ 19.02.2025):

    pip install featurewiz
    
</details> <details><summary>Show 36 hidden projects...</summary>
  • <b><a href="https://github.com/EpistasisLab/tpot">TPOT</a></b> (πŸ₯ˆ32 Β· ⭐ 10K) - A Python Automated Machine Learning tool that optimizes machine.. <code><a href="http://bit.ly/37RvQcA">❗️LGPL-3.0</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/keras-team/keras-tuner">Keras Tuner</a></b> (πŸ₯ˆ32 Β· ⭐ 2.9K Β· πŸ’€) - A Hyperparameter Tuning Library for Keras. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/scikit-optimize/scikit-optimize">scikit-optimize</a></b> (πŸ₯ˆ32 Β· ⭐ 2.8K Β· πŸ’€) - Sequential model-based optimization with a.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/microsoft/nni">NNI</a></b> (πŸ₯ˆ31 Β· ⭐ 14K Β· πŸ’€) - An open source AutoML toolkit for automate machine learning lifecycle,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/automl/auto-sklearn">auto-sklearn</a></b> (πŸ₯ˆ31 Β· ⭐ 8K Β· πŸ’€) - Automated Machine Learning with scikit-learn. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/maxpumperla/hyperas">Hyperas</a></b> (πŸ₯ˆ27 Β· ⭐ 2.2K Β· πŸ’€) - Keras + Hyperopt: A very simple wrapper for convenient.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/automl/SMAC3">SMAC3</a></b> (πŸ₯ˆ27 Β· ⭐ 1.2K Β· πŸ’€) - SMAC3: A Versatile Bayesian Optimization Package for.. <code><a href="https://tldrlegal.com/search?q=BSD-1-Clause">❗️BSD-1-Clause</a></code>
  • <b><a href="https://github.com/SheffieldML/GPyOpt">GPyOpt</a></b> (πŸ₯ˆ26 Β· ⭐ 950 Β· πŸ’€) - Gaussian Process Optimization using GPy. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/tensorflow/adanet">AdaNet</a></b> (πŸ₯ˆ24 Β· ⭐ 3.5K Β· πŸ’€) - Fast and flexible AutoML with learning guarantees. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/ClimbsRocks/auto_ml">auto_ml</a></b> (πŸ₯ˆ24 Β· ⭐ 1.7K Β· πŸ’€) - [UNMAINTAINED] Automated machine learning for analytics & production. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/autonomio/talos">Talos</a></b> (πŸ₯ˆ24 Β· ⭐ 1.6K Β· πŸ’€) - Hyperparameter Experiments with TensorFlow and Keras. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/mindsdb/lightwood">lightwood</a></b> (πŸ₯ˆ24 Β· ⭐ 490) - Lightwood is Legos for Machine Learning. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/Epistimio/orion">Orion</a></b> (πŸ₯ˆ24 Β· ⭐ 300 Β· πŸ’€) - Asynchronous Distributed Hyperparameter Optimization. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/automl/HpBandSter">HpBandSter</a></b> (πŸ₯‰22 Β· ⭐ 620 Β· πŸ’€) - a distributed Hyperband implementation on Steroids. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/AxeldeRomblay/MLBox">MLBox</a></b> (πŸ₯‰21 Β· ⭐ 1.5K Β· πŸ’€) - MLBox is a powerful Automated Machine Learning python library. <code><a href="https://tldrlegal.com/search?q=BSD-1-Clause">❗️BSD-1-Clause</a></code>
  • <b><a href="https://github.com/williamFalcon/test-tube">Test Tube</a></b> (πŸ₯‰21 Β· ⭐ 740 Β· πŸ’€) - Python library to easily log experiments and parallelize.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/Neuraxio/Neuraxle">Neuraxle</a></b> (πŸ₯‰21 Β· ⭐ 610 Β· πŸ’€) - The worlds cleanest AutoML library - Do hyperparameter tuning.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/claesenm/optunity">optunity</a></b> (πŸ₯‰21 Β· ⭐ 420 Β· πŸ’€) - optimization routines for hyperparameter tuning. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/rsteca/sklearn-deap">sklearn-deap</a></b> (πŸ₯‰20 Β· ⭐ 770 Β· πŸ’€) - Use evolutionary algorithms instead of gridsearch in.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/gugarosa/opytimizer">opytimizer</a></b> (πŸ₯‰20 Β· ⭐ 630 Β· πŸ’€) - Opytimizer is a Python library consisting of meta-heuristic.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/nidhaloff/igel">igel</a></b> (πŸ₯‰19 Β· ⭐ 3.1K Β· πŸ’€) - a delightful machine learning tool that allows you to train, test, and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/dragonfly/dragonfly">Dragonfly</a></b> (πŸ₯‰19 Β· ⭐ 890 Β· πŸ’€) - An open source python library for scalable Bayesian optimisation. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/HDI-Project/ATM">Auto Tune Models</a></b> (πŸ₯‰19 Β· ⭐ 530 Β· πŸ’€) - Auto Tune Models - A multi-tenant, multi-data system for.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/sherpa-ai/sherpa">Sherpa</a></b> (πŸ₯‰19 Β· ⭐ 340 Β· πŸ’€) - Hyperparameter optimization that enables researchers to.. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code>
  • <b><a href="https://github.com/cerlymarco/shap-hypetune">shap-hypetune</a></b> (πŸ₯‰18 Β· ⭐ 580 Β· πŸ’€) - A python package for simultaneous Hyperparameters Tuning and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/tobegit3hub/advisor">Advisor</a></b> (πŸ₯‰17 Β· ⭐ 1.6K Β· πŸ’€) - Open-source implementation of Google Vizier for hyper parameters.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/reiinakano/xcessiv">Xcessiv</a></b> (πŸ₯‰17 Β· ⭐ 1.3K Β· πŸ’€) - A web-based application for quick, scalable, and automated.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/minimaxir/automl-gs">automl-gs</a></b> (πŸ₯‰16 Β· ⭐ 1.9K Β· πŸ’€) - Provide an input CSV and a target field to predict, generate a.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/HunterMcGushion/hyperparameter_hunter">HyperparameterHunter</a></b> (πŸ₯‰16 Β· ⭐ 710 Β· πŸ’€) - Easy hyperparameter optimization and automatic result.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/jmcarpenter2/parfit">Parfit</a></b> (πŸ₯‰15 Β· ⭐ 200 Β· πŸ’€) - A package for parallelizing the fit and flexibly scoring of.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/carpedm20/ENAS-pytorch">ENAS</a></b> (πŸ₯‰13 Β· ⭐ 2.7K Β· πŸ’€) - PyTorch implementation of Efficient Neural Architecture Search via.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/LGE-ARC-AdvancedAI/auptimizer">Auptimizer</a></b> (πŸ₯‰12 Β· ⭐ 200 Β· πŸ’€) - An automatic ML model optimization tool. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code>
  • <b><a href="https://github.com/genixpro/hypermax">Hypermax</a></b> (πŸ₯‰12 Β· ⭐ 110 Β· πŸ’€) - Better, faster hyper-parameter optimization. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/google/model_search">model_search</a></b> (πŸ₯‰11 Β· ⭐ 3.3K Β· πŸ’€) - AutoML algorithms for model architecture search at scale. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/joeddav/devol">Devol</a></b> (πŸ₯‰11 Β· ⭐ 950 Β· πŸ’€) - Genetic neural architecture search with Keras. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/gdikov/hypertunity">Hypertunity</a></b> (πŸ₯‰9 Β· ⭐ 140 Β· πŸ’€) - A toolset for black-box hyperparameter optimisation. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
</details> <br>

Reinforcement Learning

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries for building and evaluating reinforcement learning & agent-based systems.

<details><summary><b><a href="https://github.com/AI4Finance-Foundation/FinRL">FinRL</a></b> (πŸ₯‡30 Β· ⭐ 13K) - FinRL: Financial Reinforcement Learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 2.9K Β· πŸ“¦ 110 Β· πŸ“‹ 760 - 35% open Β· ⏱️ 03.10.2025):

    git clone https://github.com/AI4Finance-Foundation/FinRL
    
  • PyPi (πŸ“₯ 2.8K / month Β· ⏱️ 08.01.2022):

    pip install finrl
    
</details> <details><summary><b><a href="https://github.com/Farama-Foundation/ViZDoom">ViZDoom</a></b> (πŸ₯‡29 Β· ⭐ 1.9K) - Reinforcement Learning environments based on the 1993 game Doom. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 57 Β· πŸ”€ 400 Β· πŸ“₯ 12K Β· πŸ“¦ 340 Β· πŸ“‹ 470 - 6% open Β· ⏱️ 26.10.2025):

    git clone https://github.com/mwydmuch/ViZDoom
    
  • PyPi (πŸ“₯ 6.9K / month Β· πŸ“¦ 20 Β· ⏱️ 22.10.2025):

    pip install vizdoom
    
</details> <details><summary><b><a href="https://github.com/google/dopamine">Dopamine</a></b> (πŸ₯ˆ27 Β· ⭐ 11K Β· πŸ’€) - Dopamine is a research framework for fast prototyping of.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 1.4K Β· πŸ“¦ 21 Β· πŸ“‹ 200 - 55% open Β· ⏱️ 04.11.2024):

    git clone https://github.com/google/dopamine
    
  • PyPi (πŸ“₯ 68K / month Β· πŸ“¦ 10 Β· ⏱️ 31.10.2024):

    pip install dopamine-rl
    
</details> <details><summary><b><a href="https://github.com/google-deepmind/acme">Acme</a></b> (πŸ₯ˆ27 Β· ⭐ 3.8K) - A library of reinforcement learning components and agents. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 500 Β· πŸ“¦ 250 Β· πŸ“‹ 270 - 24% open Β· ⏱️ 26.09.2025):

    git clone https://github.com/deepmind/acme
    
  • PyPi (πŸ“₯ 6.4K / month Β· πŸ“¦ 3 Β· ⏱️ 10.02.2022):

    pip install dm-acme
    
  • Conda (πŸ“₯ 14K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge dm-acme
    
</details> <details><summary><b><a href="https://github.com/tensorflow/agents">TF-Agents</a></b> (πŸ₯ˆ27 Β· ⭐ 3K) - TF-Agents: A reliable, scalable and easy to use TensorFlow.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 740 Β· πŸ“‹ 680 - 30% open Β· ⏱️ 16.06.2025):

    git clone https://github.com/tensorflow/agents
    
  • PyPi (πŸ“₯ 45K / month Β· πŸ“¦ 14 Β· ⏱️ 14.12.2023):

    pip install tf-agents
    
</details> <details><summary><b><a href="https://github.com/google-deepmind/rlax">RLax</a></b> (πŸ₯‰26 Β· ⭐ 1.4K) - A library of reinforcement learning building blocks in JAX. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 95 Β· πŸ“¦ 370 Β· πŸ“‹ 28 - 32% open Β· ⏱️ 26.09.2025):

    git clone https://github.com/deepmind/rlax
    
  • PyPi (πŸ“₯ 48K / month Β· πŸ“¦ 22 Β· ⏱️ 01.09.2025):

    pip install rlax
    
</details> <details><summary><b><a href="https://github.com/PaddlePaddle/PARL">PARL</a></b> (πŸ₯‰24 Β· ⭐ 3.4K) - A high-performance distributed training framework for Reinforcement.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1M" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 46 Β· πŸ”€ 820 Β· πŸ“¦ 140 Β· πŸ“‹ 540 - 23% open Β· ⏱️ 13.09.2025):

    git clone https://github.com/PaddlePaddle/PARL
    
  • PyPi (πŸ“₯ 770 / month Β· πŸ“¦ 1 Β· ⏱️ 13.05.2022):

    pip install parl
    
</details> <details><summary><b><a href="https://github.com/facebookresearch/ReAgent">ReAgent</a></b> (πŸ₯‰22 Β· ⭐ 3.7K) - A platform for Reasoning systems (Reinforcement Learning,.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 170 Β· πŸ”€ 520 Β· πŸ“‹ 160 - 53% open Β· ⏱️ 17.10.2025):

    git clone https://github.com/facebookresearch/ReAgent
    
  • PyPi (πŸ“₯ 50 / month Β· ⏱️ 27.05.2020):

    pip install reagent
    
</details> <details><summary>Show 15 hidden projects...</summary>
  • <b><a href="https://github.com/openai/gym">OpenAI Gym</a></b> (πŸ₯‡40 Β· ⭐ 37K Β· πŸ’€) - A toolkit for developing and comparing reinforcement learning.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/openai/baselines">baselines</a></b> (πŸ₯‡29 Β· ⭐ 17K Β· πŸ’€) - OpenAI Baselines: high-quality implementations of reinforcement.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/keras-rl/keras-rl">keras-rl</a></b> (πŸ₯ˆ28 Β· ⭐ 5.6K Β· πŸ’€) - Deep Reinforcement Learning for Keras. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/tensorlayer/TensorLayer">TensorLayer</a></b> (πŸ₯ˆ27 Β· ⭐ 7.4K Β· πŸ’€) - Deep Learning and Reinforcement Learning Library for.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/tensorforce/tensorforce">TensorForce</a></b> (πŸ₯ˆ27 Β· ⭐ 3.3K Β· πŸ’€) - Tensorforce: a TensorFlow library for applied.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/rlworkgroup/garage">garage</a></b> (πŸ₯‰26 Β· ⭐ 2K Β· πŸ’€) - A toolkit for reproducible reinforcement learning research. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/chainer/chainerrl">ChainerRL</a></b> (πŸ₯‰25 Β· ⭐ 1.2K Β· πŸ’€) - ChainerRL is a deep reinforcement learning library built on top of.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/hill-a/stable-baselines">Stable Baselines</a></b> (πŸ₯‰24 Β· ⭐ 4.3K Β· πŸ’€) - A fork of OpenAI Baselines, implementations of.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/pfnet/pfrl">PFRL</a></b> (πŸ₯‰23 Β· ⭐ 1.2K Β· πŸ’€) - PFRL: a PyTorch-based deep reinforcement learning library. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/google-deepmind/trfl">TRFL</a></b> (πŸ₯‰22 Β· ⭐ 3.1K Β· πŸ’€) - TensorFlow Reinforcement Learning. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/IntelLabs/coach">Coach</a></b> (πŸ₯‰20 Β· ⭐ 2.3K Β· πŸ’€) - Reinforcement Learning Coach by Intel AI Lab enables easy.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/SerpentAI/SerpentAI">SerpentAI</a></b> (πŸ₯‰19 Β· ⭐ 6.9K Β· πŸ’€) - Game Agent Framework. Helping you create AIs / Bots that learn to.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/google-deepmind/lab">DeepMind Lab</a></b> (πŸ₯‰17 Β· ⭐ 7.3K Β· πŸ’€) - A customisable 3D platform for agent-based AI research. <code>❗Unlicensed</code>
  • <b><a href="https://github.com/enlite-ai/maze">Maze</a></b> (πŸ₯‰12 Β· ⭐ 280 Β· πŸ’€) - Maze Applied Reinforcement Learning Framework. <code><a href="https://tldrlegal.com/search?q=Custom">❗️Custom</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/google-research/rliable">rliable</a></b> (πŸ₯‰11 Β· ⭐ 850 Β· πŸ’€) - [NeurIPS21 Outstanding Paper] Library for reliable evaluation on.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
</details> <br>

Recommender Systems

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries for building and evaluating recommendation systems.

<details><summary><b><a href="https://github.com/recommenders-team/recommenders">Recommenders</a></b> (πŸ₯‡33 Β· ⭐ 21K) - Best Practices on Recommendation Systems. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 3.2K Β· πŸ“₯ 790 Β· πŸ“¦ 180 Β· πŸ“‹ 890 - 18% open Β· ⏱️ 13.10.2025):

    git clone https://github.com/microsoft/recommenders
    
  • PyPi (πŸ“₯ 15K / month Β· πŸ“¦ 4 Β· ⏱️ 24.12.2024):

    pip install recommenders
    
</details> <details><summary><b><a href="https://github.com/meta-pytorch/torchrec">torchrec</a></b> (πŸ₯‡32 Β· ⭐ 2.4K) - Pytorch domain library for recommendation systems. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 400 Β· πŸ”€ 560 Β· πŸ“¦ 240 Β· πŸ“‹ 320 - 49% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/pytorch/torchrec
    
  • PyPi (πŸ“₯ 160 / month Β· ⏱️ 12.05.2022):

    pip install torchrec-nightly-cpu
    
</details> <details><summary><b><a href="https://github.com/PreferredAI/cornac">Cornac</a></b> (πŸ₯ˆ28 Β· ⭐ 1K) - A Comparative Framework for Multimodal Recommender Systems. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 160 Β· πŸ“¦ 300 Β· πŸ“‹ 170 - 17% open Β· ⏱️ 04.10.2025):

    git clone https://github.com/PreferredAI/cornac
    
  • PyPi (πŸ“₯ 44K / month Β· πŸ“¦ 18 Β· ⏱️ 04.10.2025):

    pip install cornac
    
  • Conda (πŸ“₯ 920K Β· ⏱️ 05.10.2025):

    conda install -c conda-forge cornac
    
</details> <details><summary><b><a href="https://github.com/lenskit/lkpy">lkpy</a></b> (πŸ₯ˆ28 Β· ⭐ 300) - Python recommendation toolkit. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 72 Β· πŸ“¦ 140 Β· πŸ“‹ 290 - 33% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/lenskit/lkpy
    
  • PyPi (πŸ“₯ 6.6K / month Β· πŸ“¦ 13 Β· ⏱️ 22.10.2025):

    pip install lenskit
    
  • Conda (πŸ“₯ 52K Β· ⏱️ 23.10.2025):

    conda install -c conda-forge lenskit
    
</details> <details><summary><b><a href="https://github.com/RUCAIBox/RecBole">RecBole</a></b> (πŸ₯‰25 Β· ⭐ 4.1K Β· πŸ’€) - A unified, comprehensive and efficient recommendation library. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 79 Β· πŸ”€ 690 Β· πŸ“‹ 1.1K - 32% open Β· ⏱️ 24.02.2025):

    git clone https://github.com/RUCAIBox/RecBole
    
  • PyPi (πŸ“₯ 98K / month Β· πŸ“¦ 2 Β· ⏱️ 24.02.2025):

    pip install recbole
    
  • Conda (πŸ“₯ 9.3K Β· ⏱️ 25.03.2025):

    conda install -c aibox recbole
    
</details> <details><summary><b><a href="https://github.com/tensorflow/recommenders">TF Recommenders</a></b> (πŸ₯‰25 Β· ⭐ 2K) - TensorFlow Recommenders is a library for building.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 290 Β· πŸ“‹ 450 - 59% open Β· ⏱️ 27.09.2025):

    git clone https://github.com/tensorflow/recommenders
    
  • PyPi (πŸ“₯ 220K / month Β· πŸ“¦ 2 Β· ⏱️ 03.02.2023):

    pip install tensorflow-recommenders
    
</details> <details><summary>Show 11 hidden projects...</summary>
  • <b><a href="https://github.com/benfred/implicit">implicit</a></b> (πŸ₯ˆ30 Β· ⭐ 3.7K Β· πŸ’€) - Fast Python Collaborative Filtering for Implicit Feedback Datasets. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/lyst/lightfm">lightfm</a></b> (πŸ₯ˆ28 Β· ⭐ 5K Β· πŸ’€) - A Python implementation of LightFM, a hybrid recommendation.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/NicolasHug/Surprise">scikit-surprise</a></b> (πŸ₯ˆ27 Β· ⭐ 6.7K Β· πŸ’€) - A Python scikit for building and analyzing recommender.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/tensorflow/ranking">TF Ranking</a></b> (πŸ₯‰26 Β· ⭐ 2.8K Β· πŸ’€) - Learning to Rank in TensorFlow. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/ibayer/fastFM">fastFM</a></b> (πŸ₯‰22 Β· ⭐ 1.1K Β· πŸ’€) - fastFM: A Library for Factorization Machines. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/jfkirk/tensorrec">tensorrec</a></b> (πŸ₯‰21 Β· ⭐ 1.3K Β· πŸ’€) - A TensorFlow recommendation algorithm and framework in.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/maciejkula/spotlight">Spotlight</a></b> (πŸ₯‰18 Β· ⭐ 3K Β· πŸ’€) - Deep recommender models using PyTorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/statisticianinstilettos/recmetrics">recmetrics</a></b> (πŸ₯‰18 Β· ⭐ 580 Β· πŸ’€) - A library of metrics for evaluating recommender systems. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/caserec/CaseRecommender">Case Recommender</a></b> (πŸ₯‰18 Β· ⭐ 500 Β· πŸ’€) - Case Recommender: A Flexible and Extensible Python.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/ylongqi/openrec">OpenRec</a></b> (πŸ₯‰16 Β· ⭐ 420 Β· πŸ’€) - OpenRec is an open-source and modular library for neural network-.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/ShopRunner/collie">Collie</a></b> (πŸ₯‰10 Β· ⭐ 100 Β· πŸ’€) - A library for preparing, training, and evaluating scalable deep.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
</details> <br>

Privacy Machine Learning

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries for encrypted and privacy-preserving machine learning using methods like federated learning & differential privacy.

<details><summary><b><a href="https://github.com/meta-pytorch/opacus">Opacus</a></b> (πŸ₯‡32 Β· ⭐ 1.9K) - Training PyTorch models with differential privacy. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 87 Β· πŸ”€ 370 Β· πŸ“₯ 150 Β· πŸ“¦ 1.2K Β· πŸ“‹ 340 - 19% open Β· ⏱️ 27.10.2025):

    git clone https://github.com/pytorch/opacus
    
  • PyPi (πŸ“₯ 92K / month Β· πŸ“¦ 49 Β· ⏱️ 27.05.2025):

    pip install opacus
    
  • Conda (πŸ“₯ 28K Β· ⏱️ 09.07.2025):

    conda install -c conda-forge opacus
    
</details> <details><summary><b><a href="https://github.com/OpenMined/PySyft">PySyft</a></b> (πŸ₯ˆ31 Β· ⭐ 9.8K) - Perform data science on data that remains in someone elses server. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 520 Β· πŸ”€ 2K Β· πŸ“₯ 2.1K Β· πŸ“¦ 1 Β· πŸ“‹ 3.4K - 1% open Β· ⏱️ 13.04.2025):

    git clone https://github.com/OpenMined/PySyft
    
  • PyPi (πŸ“₯ 32K / month Β· πŸ“¦ 5 Β· ⏱️ 13.04.2025):

    pip install syft
    
</details> <details><summary><b><a href="https://github.com/tensorflow/privacy">TensorFlow Privacy</a></b> (πŸ₯ˆ24 Β· ⭐ 2K) - Library for training machine learning models with.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 60 Β· πŸ”€ 460 Β· πŸ“₯ 190 Β· πŸ“‹ 210 - 55% open Β· ⏱️ 13.06.2025):

    git clone https://github.com/tensorflow/privacy
    
  • PyPi (πŸ“₯ 18K / month Β· πŸ“¦ 21 Β· ⏱️ 14.02.2024):

    pip install tensorflow-privacy
    
</details> <details><summary><b><a href="https://github.com/FederatedAI/FATE">FATE</a></b> (πŸ₯‰23 Β· ⭐ 6K Β· πŸ’€) - An Industrial Grade Federated Learning Framework. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 1.6K Β· πŸ“¦ 1 Β· πŸ“‹ 2.1K - 2% open Β· ⏱️ 19.11.2024):

    git clone https://github.com/FederatedAI/FATE
    
  • PyPi (⏱️ 06.05.2020):

    pip install ETAF
    
</details> <details><summary><b><a href="https://github.com/facebookresearch/CrypTen">CrypTen</a></b> (πŸ₯‰21 Β· ⭐ 1.6K Β· πŸ’€) - A framework for Privacy Preserving Machine Learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 290 Β· πŸ“‹ 280 - 28% open Β· ⏱️ 23.11.2024):

    git clone https://github.com/facebookresearch/CrypTen
    
  • PyPi (πŸ“₯ 600 / month Β· πŸ“¦ 1 Β· ⏱️ 08.12.2022):

    pip install crypten
    
</details> <details><summary>Show 2 hidden projects...</summary>
  • <b><a href="https://github.com/tf-encrypted/tf-encrypted">TFEncrypted</a></b> (πŸ₯ˆ24 Β· ⭐ 1.2K Β· πŸ’€) - A Framework for Encrypted Machine Learning in.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/OpenMined/PipelineDP">PipelineDP</a></b> (πŸ₯‰19 Β· ⭐ 280) - PipelineDP is a Python framework for applying differentially.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
</details> <br>

Workflow & Experiment Tracking

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries to organize, track, and visualize machine learning experiments.

<details><summary><b><a href="https://github.com/mlflow/mlflow">mlflow</a></b> (πŸ₯‡47 Β· ⭐ 23K) - The open source developer platform to build AI/LLM applications and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 910 Β· πŸ”€ 4.9K Β· πŸ“¦ 66K Β· πŸ“‹ 5.2K - 39% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/mlflow/mlflow
    
  • PyPi (πŸ“₯ 26M / month Β· πŸ“¦ 1.3K Β· ⏱️ 22.10.2025):

    pip install mlflow
    
  • Conda (πŸ“₯ 3.7M Β· ⏱️ 24.10.2025):

    conda install -c conda-forge mlflow
    
</details> <details><summary><b><a href="https://github.com/wandb/wandb">wandb client</a></b> (πŸ₯‡44 Β· ⭐ 10K) - The AI developer platform. Use Weights & Biases to train and fine-.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 220 Β· πŸ”€ 790 Β· πŸ“₯ 1.2K Β· πŸ“¦ 84K Β· πŸ“‹ 3.7K - 18% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/wandb/client
    
  • PyPi (πŸ“₯ 20M / month Β· πŸ“¦ 2.3K Β· ⏱️ 28.10.2025):

    pip install wandb
    
  • Conda (πŸ“₯ 1.2M Β· ⏱️ 30.10.2025):

    conda install -c conda-forge wandb
    
</details> <details><summary><b><a href="https://github.com/iterative/dvc">DVC</a></b> (πŸ₯‡42 Β· ⭐ 15K) - Data Versioning and ML Experiments. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 320 Β· πŸ”€ 1.2K Β· πŸ“¦ 24K Β· πŸ“‹ 4.9K - 4% open Β· ⏱️ 28.10.2025):

    git clone https://github.com/iterative/dvc
    
  • PyPi (πŸ“₯ 1.5M / month Β· πŸ“¦ 140 Β· ⏱️ 02.09.2025):

    pip install dvc
    
  • Conda (πŸ“₯ 3.1M Β· ⏱️ 02.09.2025):

    conda install -c conda-forge dvc
    
</details> <details><summary><b><a href="https://github.com/tensorflow/tensorboard">Tensorboard</a></b> (πŸ₯‡41 Β· ⭐ 7K) - TensorFlows Visualization Toolkit. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 330 Β· πŸ”€ 1.7K Β· πŸ“¦ 330K Β· πŸ“‹ 2K - 36% open Β· ⏱️ 12.08.2025):

    git clone https://github.com/tensorflow/tensorboard
    
  • PyPi (πŸ“₯ 31M / month Β· πŸ“¦ 2.8K Β· ⏱️ 17.07.2025):

    pip install tensorboard
    
  • Conda (πŸ“₯ 6M Β· ⏱️ 18.07.2025):

    conda install -c conda-forge tensorboard
    
</details> <details><summary><b><a href="https://github.com/aws/sagemaker-python-sdk">SageMaker SDK</a></b> (πŸ₯‡41 Β· ⭐ 2.2K) - A library for training and deploying machine learning.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1X" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 500 Β· πŸ”€ 1.2K Β· πŸ“¦ 6.2K Β· πŸ“‹ 1.6K - 21% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/aws/sagemaker-python-sdk
    
  • PyPi (πŸ“₯ 27M / month Β· πŸ“¦ 210 Β· ⏱️ 29.10.2025):

    pip install sagemaker
    
  • Conda (πŸ“₯ 1.8M Β· ⏱️ 30.10.2025):

    conda install -c conda-forge sagemaker-python-sdk
    
</details> <details><summary><b><a href="https://github.com/Netflix/metaflow">Metaflow</a></b> (πŸ₯ˆ37 Β· ⭐ 9.6K) - Build, Manage and Deploy AI/ML Systems. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 930 Β· πŸ“¦ 950 Β· πŸ“‹ 840 - 43% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/Netflix/metaflow
    
  • PyPi (πŸ“₯ 740K / month Β· πŸ“¦ 53 Β· ⏱️ 29.10.2025):

    pip install metaflow
    
  • Conda (πŸ“₯ 340K Β· ⏱️ 29.10.2025):

    conda install -c conda-forge metaflow
    
</details> <details><summary><b><a href="https://github.com/lanpa/tensorboardX">tensorboardX</a></b> (πŸ₯ˆ35 Β· ⭐ 8K) - tensorboard for pytorch (and chainer, mxnet, numpy, ...). <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 85 Β· πŸ”€ 860 Β· πŸ“₯ 500 Β· πŸ“¦ 60K Β· πŸ“‹ 470 - 18% open Β· ⏱️ 13.06.2025):

    git clone https://github.com/lanpa/tensorboardX
    
  • PyPi (πŸ“₯ 4.5M / month Β· πŸ“¦ 740 Β· ⏱️ 10.06.2025):

    pip install tensorboardX
    
  • Conda (πŸ“₯ 1.3M Β· ⏱️ 22.04.2025):

    conda install -c conda-forge tensorboardx
    
</details> <details><summary><b><a href="https://github.com/pycaret/pycaret">PyCaret</a></b> (πŸ₯ˆ34 Β· ⭐ 9.6K Β· πŸ’€) - An open-source, low-code machine learning library in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.8K Β· πŸ“₯ 730 Β· πŸ“¦ 7.9K Β· πŸ“‹ 2.3K - 16% open Β· ⏱️ 06.03.2025):

    git clone https://github.com/pycaret/pycaret
    
  • PyPi (πŸ“₯ 310K / month Β· πŸ“¦ 31 Β· ⏱️ 28.04.2024):

    pip install pycaret
    
  • Conda (πŸ“₯ 78K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge pycaret
    
</details> <details><summary><b><a href="https://github.com/clearml/clearml">ClearML</a></b> (πŸ₯ˆ34 Β· ⭐ 6.3K) - ClearML - Auto-Magical CI/CD to streamline your AI workload... <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 710 Β· πŸ“₯ 3.5K Β· πŸ“¦ 1.9K Β· πŸ“‹ 1.2K - 45% open Β· ⏱️ 27.10.2025):

    git clone https://github.com/allegroai/clearml
    
  • PyPi (πŸ“₯ 500K / month Β· πŸ“¦ 78 Β· ⏱️ 22.10.2025):

    pip install clearml
    
  • Docker Hub (πŸ“₯ 31K Β· ⏱️ 05.10.2020):

    docker pull allegroai/trains
    
</details> <details><summary><b><a href="https://github.com/snakemake/snakemake">snakemake</a></b> (πŸ₯ˆ34 Β· ⭐ 2.6K) - This is the development home of the workflow management system.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 380 Β· πŸ”€ 610 Β· πŸ“¦ 2.5K Β· πŸ“‹ 2.1K - 58% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/snakemake/snakemake
    
  • PyPi (πŸ“₯ 130K / month Β· πŸ“¦ 320 Β· ⏱️ 22.10.2025):

    pip install snakemake
    
  • Conda (πŸ“₯ 1.5M Β· ⏱️ 28.10.2025):

    conda install -c bioconda snakemake
    
</details> <details><summary><b><a href="https://github.com/Kaggle/kaggle-api">kaggle</a></b> (πŸ₯ˆ33 Β· ⭐ 6.9K) - Official Kaggle API. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 49 Β· πŸ”€ 1.2K Β· πŸ“¦ 21 Β· πŸ“‹ 530 - 27% open Β· ⏱️ 28.10.2025):

    git clone https://github.com/Kaggle/kaggle-api
    
  • PyPi (πŸ“₯ 610K / month Β· πŸ“¦ 240 Β· ⏱️ 08.05.2025):

    pip install kaggle
    
  • Conda (πŸ“₯ 250K Β· ⏱️ 11.08.2025):

    conda install -c conda-forge kaggle
    
</details> <details><summary><b><a href="https://github.com/aimhubio/aim">aim</a></b> (πŸ₯ˆ32 Β· ⭐ 5.8K) - Aim An easy-to-use & supercharged open-source experiment tracker. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 360 Β· πŸ“¦ 1.1K Β· πŸ“‹ 1.1K - 37% open Β· ⏱️ 26.06.2025):

    git clone https://github.com/aimhubio/aim
    
  • PyPi (πŸ“₯ 120K / month Β· πŸ“¦ 56 Β· ⏱️ 11.06.2025):

    pip install aim
    
  • Conda (πŸ“₯ 140K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge aim
    
</details> <details><summary><b><a href="https://github.com/Azure/MachineLearningNotebooks">AzureML SDK</a></b> (πŸ₯ˆ31 Β· ⭐ 4.3K Β· πŸ’€) - Python notebooks with ML and deep learning examples with Azure.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 65 Β· πŸ”€ 2.5K Β· πŸ“₯ 680 Β· πŸ“‹ 1.5K - 26% open Β· ⏱️ 14.03.2025):

    git clone https://github.com/Azure/MachineLearningNotebooks
    
  • PyPi (πŸ“₯ 2.2M / month Β· πŸ“¦ 31 Β· ⏱️ 11.04.2025):

    pip install azureml-sdk
    
</details> <details><summary><b><a href="https://github.com/PaddlePaddle/VisualDL">VisualDL</a></b> (πŸ₯ˆ29 Β· ⭐ 4.9K Β· πŸ’€) - Deep Learning Visualization Toolkit. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1M" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 36 Β· πŸ”€ 630 Β· πŸ“₯ 540 Β· πŸ“¦ 3.6K Β· πŸ“‹ 510 - 30% open Β· ⏱️ 22.01.2025):

    git clone https://github.com/PaddlePaddle/VisualDL
    
  • PyPi (πŸ“₯ 170K / month Β· πŸ“¦ 82 Β· ⏱️ 30.10.2024):

    pip install visualdl
    
</details> <details><summary><b><a href="https://github.com/IDSIA/sacred">sacred</a></b> (πŸ₯ˆ29 Β· ⭐ 4.3K) - Sacred is a tool to help you configure, organize, log and reproduce.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 390 Β· πŸ“¦ 3.6K Β· πŸ“‹ 560 - 18% open Β· ⏱️ 22.10.2025):

    git clone https://github.com/IDSIA/sacred
    
  • PyPi (πŸ“₯ 48K / month Β· πŸ“¦ 60 Β· ⏱️ 26.11.2024):

    pip install sacred
    
  • Conda (πŸ“₯ 9.9K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge sacred
    
</details> <details><summary><b><a href="https://github.com/neptune-ai/neptune-client">Neptune.ai</a></b> (πŸ₯ˆ29 Β· ⭐ 620) - The experiment tracker for foundation model training. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 57 Β· πŸ”€ 66 Β· πŸ“¦ 920 Β· πŸ“‹ 260 - 12% open Β· ⏱️ 09.06.2025):

    git clone https://github.com/neptune-ai/neptune-client
    
  • PyPi (πŸ“₯ 480K / month Β· πŸ“¦ 77 Β· ⏱️ 15.04.2025):

    pip install neptune-client
    
  • Conda (πŸ“₯ 390K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge neptune-client
    
</details> <details><summary><b><a href="https://github.com/meta-pytorch/tnt">TNT</a></b> (πŸ₯‰28 Β· ⭐ 1.7K) - A lightweight library for PyTorch training tools and utilities. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 290 Β· πŸ“‹ 150 - 56% open Β· ⏱️ 09.10.2025):

    git clone https://github.com/pytorch/tnt
    
  • PyPi (πŸ“₯ 9.4K / month Β· πŸ“¦ 24 Β· ⏱️ 29.07.2018):

    pip install torchnet
    
</details> <details><summary><b><a href="https://github.com/stared/livelossplot">livelossplot</a></b> (πŸ₯‰25 Β· ⭐ 1.3K Β· πŸ’€) - Live training loss plot in Jupyter Notebook for Keras,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 140 Β· πŸ“¦ 1.9K Β· πŸ“‹ 79 - 7% open Β· ⏱️ 03.01.2025):

    git clone https://github.com/stared/livelossplot
    
  • PyPi (πŸ“₯ 19K / month Β· πŸ“¦ 16 Β· ⏱️ 03.01.2025):

    pip install livelossplot
    
</details> <details><summary><b><a href="https://github.com/google/ml-metadata">ml-metadata</a></b> (πŸ₯‰25 Β· ⭐ 660) - For recording and retrieving metadata associated with ML.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 170 Β· πŸ“₯ 3K Β· πŸ“¦ 720 Β· πŸ“‹ 130 - 41% open Β· ⏱️ 03.04.2025):

    git clone https://github.com/google/ml-metadata
    
  • PyPi (πŸ“₯ 50K / month Β· πŸ“¦ 32 Β· ⏱️ 07.04.2025):

    pip install ml-metadata
    
</details> <details><summary><b><a href="https://github.com/labmlai/labml">Labml</a></b> (πŸ₯‰24 Β· ⭐ 2.3K) - Monitor deep learning model training and hardware usage from your mobile.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 140 Β· πŸ“¦ 240 Β· πŸ“‹ 50 - 12% open Β· ⏱️ 10.04.2025):

    git clone https://github.com/labmlai/labml
    
  • PyPi (πŸ“₯ 4.6K / month Β· πŸ“¦ 14 Β· ⏱️ 15.09.2024):

    pip install labml
    
</details> <details><summary><b><a href="https://github.com/mrpowers-io/quinn">quinn</a></b> (πŸ₯‰24 Β· ⭐ 680 Β· πŸ’€) - pyspark methods to enhance developer productivity. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 98 Β· πŸ“₯ 69 Β· πŸ“¦ 94 Β· πŸ“‹ 130 - 27% open Β· ⏱️ 06.12.2024):

    git clone https://github.com/MrPowers/quinn
    
  • PyPi (πŸ“₯ 750K / month Β· πŸ“¦ 7 Β· ⏱️ 13.02.2024):

    pip install quinn
    
</details> <details><summary><b><a href="https://github.com/m3dev/gokart">gokart</a></b> (πŸ₯‰24 Β· ⭐ 330) - Gokart solves reproducibility, task dependencies, constraints of good code,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 63 Β· πŸ“¦ 85 Β· πŸ“‹ 100 - 31% open Β· ⏱️ 18.06.2025):

    git clone https://github.com/m3dev/gokart
    
  • PyPi (πŸ“₯ 6.7K / month Β· πŸ“¦ 8 Β· ⏱️ 18.06.2025):

    pip install gokart
    
</details> <details><summary><b><a href="https://github.com/guildai/guildai">Guild AI</a></b> (πŸ₯‰23 Β· ⭐ 890) - Experiment tracking, ML developer tools. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 30 Β· πŸ”€ 90 Β· πŸ“₯ 32 Β· πŸ“¦ 110 Β· πŸ“‹ 440 - 50% open Β· ⏱️ 29.04.2025):

    git clone https://github.com/guildai/guildai
    
  • PyPi (πŸ“₯ 1.7K / month Β· ⏱️ 11.05.2022):

    pip install guildai
    
</details> <details><summary><b><a href="https://github.com/microsoft/tensorwatch">TensorWatch</a></b> (πŸ₯‰22 Β· ⭐ 3.5K) - Debugging, monitoring and visualization for Python Machine Learning.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 15 Β· πŸ”€ 360 Β· πŸ“¦ 160 Β· πŸ“‹ 70 - 75% open Β· ⏱️ 27.09.2025):

    git clone https://github.com/microsoft/tensorwatch
    
  • PyPi (πŸ“₯ 1.4K / month Β· πŸ“¦ 7 Β· ⏱️ 04.03.2020):

    pip install tensorwatch
    
</details> <details><summary><b><a href="https://github.com/replicate/keepsake">keepsake</a></b> (πŸ₯‰18 Β· ⭐ 1.7K Β· πŸ’€) - Version control for machine learning. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 71 Β· πŸ“‹ 190 - 65% open Β· ⏱️ 03.12.2024):

    git clone https://github.com/replicate/keepsake
    
  • PyPi (πŸ“₯ 880 / month Β· πŸ“¦ 1 Β· ⏱️ 25.01.2021):

    pip install keepsake
    
</details> <details><summary><b><a href="https://github.com/datmo/datmo">datmo</a></b> (πŸ₯‰17 Β· ⭐ 340) - Open source production model management tool for data scientists. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 30 Β· πŸ“¦ 7 Β· πŸ“‹ 180 - 17% open Β· ⏱️ 23.06.2025):

    git clone https://github.com/datmo/datmo
    
  • PyPi (πŸ“₯ 130 / month Β· ⏱️ 07.12.2018):

    pip install datmo
    
</details> <details><summary><b><a href="https://www.comet.com">CometML</a></b> (πŸ₯‰16) - Supercharging Machine Learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub:

    git clone https://github.com/comet-ml/examples
    
  • PyPi (πŸ“₯ 570K / month Β· πŸ“¦ 100 Β· ⏱️ 29.10.2025):

    pip install comet_ml
    
  • Conda:

    conda install -c anaconda comet_ml
    
</details> <details><summary>Show 13 hidden projects...</summary>
  • <b><a href="https://github.com/catalyst-team/catalyst">Catalyst</a></b> (πŸ₯‰28 Β· ⭐ 3.4K Β· πŸ’€) - Accelerated deep learning R&D. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/huggingface/knockknock">knockknock</a></b> (πŸ₯‰25 Β· ⭐ 2.8K Β· πŸ’€) - Knock Knock: Get notified when your training ends with only two.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/waleedka/hiddenlayer">hiddenlayer</a></b> (πŸ₯‰22 Β· ⭐ 1.9K Β· πŸ’€) - Neural network graphs and training metrics for.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/EducationalTestingService/skll">SKLL</a></b> (πŸ₯‰22 Β· ⭐ 560 Β· πŸ’€) - SciKit-Learn Laboratory (SKLL) makes it easy to run machine.. <code>❗Unlicensed</code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/TeamHG-Memex/tensorboard_logger">TensorBoard Logger</a></b> (πŸ₯‰21 Β· ⭐ 630 Β· πŸ’€) - Log TensorBoard events without touching TensorFlow. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/studioml/studio">Studio.ml</a></b> (πŸ₯‰21 Β· ⭐ 380 Β· πŸ’€) - Studio: Simplify and expedite model building process. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/instacart/lore">lore</a></b> (πŸ₯‰20 Β· ⭐ 1.5K Β· πŸ’€) - Lore makes machine learning approachable for Software Engineers and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/aniketmaurya/chitra">chitra</a></b> (πŸ₯‰17 Β· ⭐ 230) - A multi-functional library for full-stack Deep Learning. Simplifies.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/minerva-ml/steppy">steppy</a></b> (πŸ₯‰17 Β· ⭐ 140 Β· πŸ’€) - Lightweight, Python library for fast and reproducible experimentation. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/awslabs/mxboard">MXBoard</a></b> (πŸ₯‰16 Β· ⭐ 320 Β· πŸ’€) - Logging MXNet data for visualization in TensorBoard. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1X" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/google/caliban">caliban</a></b> (πŸ₯‰15 Β· ⭐ 500 Β· πŸ’€) - Research workflows made easy, locally and in the Cloud. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/ModelChimp/modelchimp">ModelChimp</a></b> (πŸ₯‰12 Β· ⭐ 130 Β· πŸ’€) - Experiment tracking for machine and deep learning projects. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code>
  • <b><a href="https://github.com/jrieke/traintool">traintool</a></b> (πŸ₯‰8 Β· ⭐ 12 Β· πŸ’€) - Train off-the-shelf machine learning models in one.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
</details> <br>

Model Serialization & Deployment

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries to serialize models to files, convert between a variety of model formats, and optimize models for deployment.

<details><summary><b><a href="https://github.com/triton-lang/triton">triton</a></b> (πŸ₯‡45 Β· ⭐ 17K) - Development repository for the Triton language and compiler. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 480 Β· πŸ”€ 2.3K Β· πŸ“₯ 1.4K Β· πŸ“¦ 74K Β· πŸ“‹ 2K - 41% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/openai/triton
    
  • PyPi (πŸ“₯ 41M / month Β· πŸ“¦ 540 Β· ⏱️ 13.10.2025):

    pip install triton
    
</details> <details><summary><b><a href="https://github.com/onnx/onnx">onnx</a></b> (πŸ₯‡43 Β· ⭐ 20K) - Open standard for machine learning interoperability. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 360 Β· πŸ”€ 3.8K Β· πŸ“₯ 25K Β· πŸ“¦ 49K Β· πŸ“‹ 3.1K - 9% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/onnx/onnx
    
  • PyPi (πŸ“₯ 13M / month Β· πŸ“¦ 1.6K Β· ⏱️ 10.10.2025):

    pip install onnx
    
  • Conda (πŸ“₯ 2.1M Β· ⏱️ 11.10.2025):

    conda install -c conda-forge onnx
    
</details> <details><summary><b><a href="https://github.com/huggingface/huggingface_hub">huggingface_hub</a></b> (πŸ₯ˆ40 Β· ⭐ 3K) - The official Python client for the Hugging Face Hub. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 280 Β· πŸ”€ 830 Β· πŸ“‹ 1.3K - 11% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/huggingface/huggingface_hub
    
  • PyPi (πŸ“₯ 120M / month Β· πŸ“¦ 4.1K Β· ⏱️ 28.10.2025):

    pip install huggingface_hub
    
  • Conda (πŸ“₯ 4.2M Β· ⏱️ 28.10.2025):

    conda install -c conda-forge huggingface_hub
    
</details> <details><summary><b><a href="https://github.com/bentoml/BentoML">BentoML</a></b> (πŸ₯ˆ36 Β· ⭐ 8.2K) - The easiest way to serve AI apps and models - Build Model Inference.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 880 Β· πŸ“₯ 95 Β· πŸ“¦ 2.8K Β· πŸ“‹ 1.1K - 11% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/bentoml/BentoML
    
  • PyPi (πŸ“₯ 180K / month Β· πŸ“¦ 44 Β· ⏱️ 29.10.2025):

    pip install bentoml
    
</details> <details><summary><b><a href="https://github.com/apple/coremltools">Core ML Tools</a></b> (πŸ₯ˆ35 Β· ⭐ 5K) - Core ML tools contain supporting tools for Core ML model.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 200 Β· πŸ”€ 710 Β· πŸ“₯ 15K Β· πŸ“¦ 5.1K Β· πŸ“‹ 1.6K - 26% open Β· ⏱️ 22.09.2025):

    git clone https://github.com/apple/coremltools
    
  • PyPi (πŸ“₯ 1.1M / month Β· πŸ“¦ 110 Β· ⏱️ 28.07.2025):

    pip install coremltools
    
  • Conda (πŸ“₯ 110K Β· ⏱️ 02.10.2025):

    conda install -c conda-forge coremltools
    
</details> <details><summary><b><a href="https://github.com/pytorch/serve">TorchServe</a></b> (πŸ₯ˆ33 Β· ⭐ 4.4K Β· πŸ’€) - Serve, optimize and scale PyTorch models in production. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 220 Β· πŸ”€ 890 Β· πŸ“₯ 8K Β· πŸ“¦ 900 Β· πŸ“‹ 1.7K - 25% open Β· ⏱️ 17.03.2025):

    git clone https://github.com/pytorch/serve
    
  • PyPi (πŸ“₯ 97K / month Β· πŸ“¦ 26 Β· ⏱️ 30.09.2024):

    pip install torchserve
    
  • Conda (πŸ“₯ 570K Β· ⏱️ 25.03.2025):

    conda install -c pytorch torchserve
    
  • Docker Hub (πŸ“₯ 1.5M Β· ⭐ 32 Β· ⏱️ 30.09.2024):

    docker pull pytorch/torchserve
    
</details> <details><summary><b><a href="https://github.com/fastmachinelearning/hls4ml">hls4ml</a></b> (πŸ₯ˆ28 Β· ⭐ 1.7K) - Machine learning on FPGAs using HLS. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 440 Β· πŸ“¦ 51 Β· πŸ“‹ 480 - 41% open Β· ⏱️ 20.10.2025):

    git clone https://github.com/fastmachinelearning/hls4ml
    
  • PyPi (πŸ“₯ 1.7K / month Β· πŸ“¦ 1 Β· ⏱️ 17.03.2025):

    pip install hls4ml
    
  • Conda (πŸ“₯ 12K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge hls4ml
    
</details> <details><summary><b><a href="https://github.com/microsoft/MMdnn">mmdnn</a></b> (πŸ₯ˆ25 Β· ⭐ 5.8K) - MMdnn is a set of tools to help users inter-operate among different deep.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 86 Β· πŸ”€ 960 Β· πŸ“₯ 4K Β· πŸ“¦ 160 Β· πŸ“‹ 630 - 53% open Β· ⏱️ 07.08.2025):

    git clone https://github.com/Microsoft/MMdnn
    
  • PyPi (πŸ“₯ 320 / month Β· ⏱️ 24.07.2020):

    pip install mmdnn
    
</details> <details><summary><b><a href="https://github.com/microsoft/hummingbird">Hummingbird</a></b> (πŸ₯‰24 Β· ⭐ 3.5K) - Hummingbird compiles trained ML models into tensor computation for.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 290 Β· πŸ“₯ 930 Β· πŸ“‹ 330 - 21% open Β· ⏱️ 17.07.2025):

    git clone https://github.com/microsoft/hummingbird
    
  • PyPi (πŸ“₯ 7.6K / month Β· πŸ“¦ 7 Β· ⏱️ 25.10.2024):

    pip install hummingbird-ml
    
  • Conda (πŸ“₯ 64K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge hummingbird-ml
    
</details> <details><summary><b><a href="https://github.com/riga/tfdeploy">tfdeploy</a></b> (πŸ₯‰15 Β· ⭐ 360 Β· πŸ’€) - Deploy tensorflow graphs for fast evaluation and export to.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 4 Β· πŸ”€ 38 Β· πŸ“‹ 34 - 32% open Β· ⏱️ 04.01.2025):

    git clone https://github.com/riga/tfdeploy
    
  • PyPi (πŸ“₯ 100 / month Β· ⏱️ 30.03.2017):

    pip install tfdeploy
    
</details> <details><summary>Show 10 hidden projects...</summary>
  • <b><a href="https://github.com/BayesWitnesses/m2cgen">m2cgen</a></b> (πŸ₯ˆ25 Β· ⭐ 2.9K Β· πŸ’€) - Transform ML models into a native code (Java, C, Python, Go,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/nok/sklearn-porter">sklearn-porter</a></b> (πŸ₯‰23 Β· ⭐ 1.3K Β· πŸ’€) - Transpile trained scikit-learn estimators to C, Java,.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/cortexlabs/cortex">cortex</a></b> (πŸ₯‰22 Β· ⭐ 8K Β· πŸ’€) - Production infrastructure for machine learning at scale. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/nebuly-ai/optimate">nebullvm</a></b> (πŸ₯‰21 Β· ⭐ 8.4K Β· πŸ’€) - A collection of libraries to optimise AI model performances. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/larq/compute-engine">Larq Compute Engine</a></b> (πŸ₯‰20 Β· ⭐ 250) - Highly optimized inference engine for Binarized.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/gmalivenko/pytorch2keras">pytorch2keras</a></b> (πŸ₯‰19 Β· ⭐ 860 Β· πŸ’€) - PyTorch to Keras model convertor. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/cog-imperial/OMLT">OMLT</a></b> (πŸ₯‰19 Β· ⭐ 340) - Represent trained machine learning models as Pyomo optimization.. <code>❗Unlicensed</code>
  • <b><a href="https://github.com/Cornerstone-OnDemand/modelkit">modelkit</a></b> (πŸ₯‰17 Β· ⭐ 150 Β· πŸ’€) - Toolkit for developing and maintaining ML models. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/backprop-ai/backprop">backprop</a></b> (πŸ₯‰14 Β· ⭐ 240 Β· πŸ’€) - Backprop makes it simple to use, finetune, and deploy state-of-.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/apple/ml-ane-transformers">ml-ane-transformers</a></b> (πŸ₯‰13 Β· ⭐ 2.7K Β· πŸ’€) - Reference implementation of the Transformer.. <code>❗Unlicensed</code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
</details> <br>

Model Interpretability

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries to visualize, explain, debug, evaluate, and interpret machine learning models.

<details><summary><b><a href="https://github.com/shap/shap">shap</a></b> (πŸ₯‡42 Β· ⭐ 25K) - A game theoretic approach to explain the output of any machine learning model. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 280 Β· πŸ”€ 3.4K Β· πŸ“¦ 36K Β· πŸ“‹ 2.7K - 23% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/slundberg/shap
    
  • PyPi (πŸ“₯ 9.5M / month Β· πŸ“¦ 1.2K Β· ⏱️ 14.10.2025):

    pip install shap
    
  • Conda (πŸ“₯ 7.5M Β· ⏱️ 17.06.2025):

    conda install -c conda-forge shap
    
</details> <details><summary><b><a href="https://github.com/arviz-devs/arviz">arviz</a></b> (πŸ₯‡37 Β· ⭐ 1.7K) - Exploratory analysis of Bayesian models with Python. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 460 Β· πŸ“₯ 190 Β· πŸ“¦ 11K Β· πŸ“‹ 900 - 19% open Β· ⏱️ 22.10.2025):

    git clone https://github.com/arviz-devs/arviz
    
  • PyPi (πŸ“₯ 3.7M / month Β· πŸ“¦ 410 Β· ⏱️ 09.07.2025):

    pip install arviz
    
  • Conda (πŸ“₯ 2.5M Β· ⏱️ 10.07.2025):

    conda install -c conda-forge arviz
    
</details> <details><summary><b><a href="https://github.com/lutzroeder/netron">Netron</a></b> (πŸ₯‡36 Β· ⭐ 32K) - Visualizer for neural network, deep learning and machine learning.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 2 Β· πŸ”€ 3K Β· πŸ“₯ 160K Β· πŸ“¦ 13 Β· πŸ“‹ 1.2K - 1% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/lutzroeder/netron
    
  • PyPi (πŸ“₯ 43K / month Β· πŸ“¦ 92 Β· ⏱️ 23.10.2025):

    pip install netron
    
</details> <details><summary><b><a href="https://github.com/huggingface/evaluate">evaluate</a></b> (πŸ₯‡34 Β· ⭐ 2.4K) - Evaluate: A library for easily evaluating machine learning models.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 290 Β· πŸ“¦ 24K Β· πŸ“‹ 390 - 62% open Β· ⏱️ 25.09.2025):

    git clone https://github.com/huggingface/evaluate
    
  • PyPi (πŸ“₯ 3.6M / month Β· πŸ“¦ 660 Β· ⏱️ 18.09.2025):

    pip install evaluate
    
</details> <details><summary><b><a href="https://github.com/interpretml/interpret">InterpretML</a></b> (πŸ₯‡33 Β· ⭐ 6.7K) - Fit interpretable models. Explain blackbox machine learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 53 Β· πŸ”€ 770 Β· πŸ“¦ 930 Β· πŸ“‹ 490 - 22% open Β· ⏱️ 24.10.2025):

    git clone https://github.com/interpretml/interpret
    
  • PyPi (πŸ“₯ 230K / month Β· πŸ“¦ 58 Β· ⏱️ 14.10.2025):

    pip install interpret
    
</details> <details><summary><b><a href="https://github.com/meta-pytorch/captum">Captum</a></b> (πŸ₯‡33 Β· ⭐ 5.4K) - Model interpretability and understanding for PyTorch. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 540 Β· πŸ“¦ 3.5K Β· πŸ“‹ 610 - 41% open Β· ⏱️ 23.10.2025):

    git clone https://github.com/pytorch/captum
    
  • PyPi (πŸ“₯ 330K / month Β· πŸ“¦ 170 Β· ⏱️ 27.03.2025):

    pip install captum
    
  • Conda (πŸ“₯ 130K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge captum
    
</details> <details><summary><b><a href="https://github.com/py-why/dowhy">DoWhy</a></b> (πŸ₯ˆ30 Β· ⭐ 7.8K) - DoWhy is a Python library for causal inference that supports explicit.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 980 Β· πŸ“₯ 43 Β· πŸ“¦ 660 Β· πŸ“‹ 510 - 27% open Β· ⏱️ 28.10.2025):

    git clone https://github.com/py-why/dowhy
    
  • PyPi (πŸ“₯ 83K / month Β· πŸ“¦ 28 Β· ⏱️ 12.07.2025):

    pip install dowhy
    
  • Conda (πŸ“₯ 51K Β· ⏱️ 13.07.2025):

    conda install -c conda-forge dowhy
    
</details> <details><summary><b><a href="https://github.com/MAIF/shapash">shapash</a></b> (πŸ₯ˆ30 Β· ⭐ 3K) - Shapash: User-friendly Explainability and Interpretability to.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 350 Β· πŸ“¦ 200 Β· πŸ“‹ 240 - 16% open Β· ⏱️ 03.10.2025):

    git clone https://github.com/MAIF/shapash
    
  • PyPi (πŸ“₯ 7.5K / month Β· πŸ“¦ 4 Β· ⏱️ 24.07.2025):

    pip install shapash
    
</details> <details><summary><b><a href="https://github.com/oegedijk/explainerdashboard">explainerdashboard</a></b> (πŸ₯ˆ30 Β· ⭐ 2.5K) - Quickly build Explainable AI dashboards that show the inner.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 340 Β· πŸ“¦ 650 Β· πŸ“‹ 240 - 16% open Β· ⏱️ 01.08.2025):

    git clone https://github.com/oegedijk/explainerdashboard
    
  • PyPi (πŸ“₯ 42K / month Β· πŸ“¦ 15 Β· ⏱️ 03.06.2025):

    pip install explainerdashboard
    
  • Conda (πŸ“₯ 75K Β· ⏱️ 04.06.2025):

    conda install -c conda-forge explainerdashboard
    
</details> <details><summary><b><a href="https://github.com/fairlearn/fairlearn">fairlearn</a></b> (πŸ₯ˆ30 Β· ⭐ 2.1K) - A Python package to assess and improve fairness of machine.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 100 Β· πŸ”€ 470 Β· πŸ“¦ 3 Β· πŸ“‹ 520 - 24% open Β· ⏱️ 27.10.2025):

    git clone https://github.com/fairlearn/fairlearn
    
  • PyPi (πŸ“₯ 160K / month Β· πŸ“¦ 80 Β· ⏱️ 19.10.2025):

    pip install fairlearn
    
  • Conda (πŸ“₯ 55K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge fairlearn
    
</details> <details><summary><b><a href="https://github.com/parrt/dtreeviz">dtreeviz</a></b> (πŸ₯ˆ28 Β· ⭐ 3.1K Β· πŸ’€) - A python library for decision tree visualization and model.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 340 Β· πŸ“¦ 1.6K Β· πŸ“‹ 210 - 35% open Β· ⏱️ 06.03.2025):

    git clone https://github.com/parrt/dtreeviz
    
  • PyPi (πŸ“₯ 110K / month Β· πŸ“¦ 53 Β· ⏱️ 07.07.2022):

    pip install dtreeviz
    
  • Conda (πŸ“₯ 120K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge dtreeviz
    
</details> <details><summary><b><a href="https://github.com/tensorflow/model-analysis">Model Analysis</a></b> (πŸ₯ˆ27 Β· ⭐ 1.3K) - Model analysis tools for TensorFlow. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 61 Β· πŸ”€ 280 Β· πŸ“‹ 97 - 39% open Β· ⏱️ 06.08.2025):

    git clone https://github.com/tensorflow/model-analysis
    
  • PyPi (πŸ“₯ 200K / month Β· πŸ“¦ 20 Β· ⏱️ 23.06.2025):

    pip install tensorflow-model-analysis
    
</details> <details><summary><b><a href="https://github.com/Trusted-AI/AIF360">Fairness 360</a></b> (πŸ₯ˆ26 Β· ⭐ 2.7K) - A comprehensive set of fairness metrics for datasets and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 73 Β· πŸ”€ 870 Β· πŸ“¦ 740 Β· πŸ“‹ 300 - 65% open Β· ⏱️ 16.10.2025):

    git clone https://github.com/Trusted-AI/AIF360
    
  • PyPi (πŸ“₯ 29K / month Β· πŸ“¦ 32 Β· ⏱️ 08.04.2024):

    pip install aif360
    
  • Conda (πŸ“₯ 29K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge aif360
    
</details> <details><summary><b><a href="https://github.com/csinva/imodels">imodels</a></b> (πŸ₯ˆ26 Β· ⭐ 1.5K) - Interpretable ML package for concise, transparent, and accurate.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 27 Β· πŸ”€ 130 Β· πŸ“¦ 130 Β· πŸ“‹ 98 - 38% open Β· ⏱️ 26.08.2025):

    git clone https://github.com/csinva/imodels
    
  • PyPi (πŸ“₯ 30K / month Β· πŸ“¦ 12 Β· ⏱️ 26.08.2025):

    pip install imodels
    
</details> <details><summary><b><a href="https://github.com/PAIR-code/lit">LIT</a></b> (πŸ₯‰25 Β· ⭐ 3.6K Β· πŸ’€) - The Learning Interpretability Tool: Interactively analyze ML models.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 38 Β· πŸ”€ 360 Β· πŸ“‹ 210 - 57% open Β· ⏱️ 20.12.2024):

    git clone https://github.com/PAIR-code/lit
    
  • PyPi (πŸ“₯ 11K / month Β· πŸ“¦ 3 Β· ⏱️ 20.12.2024):

    pip install lit-nlp
    
  • Conda (πŸ“₯ 130K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge lit-nlp
    
</details> <details><summary><b><a href="https://github.com/microsoft/responsible-ai-toolbox">responsible-ai-widgets</a></b> (πŸ₯‰25 Β· ⭐ 1.6K Β· πŸ’€) - Responsible AI Toolbox is a suite of tools providing.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 43 Β· πŸ”€ 430 Β· πŸ“‹ 330 - 28% open Β· ⏱️ 07.02.2025):

    git clone https://github.com/microsoft/responsible-ai-toolbox
    
  • PyPi (πŸ“₯ 10K / month Β· πŸ“¦ 6 Β· ⏱️ 08.07.2024):

    pip install raiwidgets
    
</details> <details><summary><b><a href="https://github.com/dssg/aequitas">aequitas</a></b> (πŸ₯‰25 Β· ⭐ 730 Β· πŸ’€) - Bias Auditing & Fair ML Toolkit. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 120 Β· πŸ“¦ 200 Β· πŸ“‹ 99 - 51% open Β· ⏱️ 25.03.2025):

    git clone https://github.com/dssg/aequitas
    
  • PyPi (πŸ“₯ 19K / month Β· πŸ“¦ 8 Β· ⏱️ 30.01.2024):

    pip install aequitas
    
</details> <details><summary><b><a href="https://github.com/Trusted-AI/AIX360">Explainability 360</a></b> (πŸ₯‰24 Β· ⭐ 1.7K Β· πŸ’€) - Interpretability and explainability of data and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 41 Β· πŸ”€ 310 Β· πŸ“¦ 170 Β· πŸ“‹ 86 - 62% open Β· ⏱️ 26.02.2025):

    git clone https://github.com/Trusted-AI/AIX360
    
  • PyPi (πŸ“₯ 1.8K / month Β· πŸ“¦ 1 Β· ⏱️ 31.07.2023):

    pip install aix360
    
</details> <details><summary><b><a href="https://github.com/philipperemy/keract">keract</a></b> (πŸ₯‰24 Β· ⭐ 1.1K) - Layers Outputs and Gradients in Keras. Made easy. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 190 Β· πŸ“¦ 260 Β· πŸ“‹ 89 - 3% open Β· ⏱️ 07.04.2025):

    git clone https://github.com/philipperemy/keract
    
  • PyPi (πŸ“₯ 8.8K / month Β· πŸ“¦ 7 Β· ⏱️ 07.04.2025):

    pip install keract
    
</details> <details><summary><b><a href="https://github.com/interpretml/DiCE">DiCE</a></b> (πŸ₯‰23 Β· ⭐ 1.5K) - Generate Diverse Counterfactual Explanations for any machine.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 210 Β· πŸ“‹ 190 - 49% open Β· ⏱️ 13.07.2025):

    git clone https://github.com/interpretml/DiCE
    
  • PyPi (πŸ“₯ 48K / month Β· πŸ“¦ 13 Β· ⏱️ 13.07.2025):

    pip install dice-ml
    
</details> <details><summary><b><a href="https://github.com/aerdem4/lofo-importance">LOFO</a></b> (πŸ₯‰19 Β· ⭐ 840 Β· πŸ’€) - Leave One Feature Out Importance. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 87 Β· πŸ“¦ 42 Β· πŸ“‹ 30 - 13% open Β· ⏱️ 14.02.2025):

    git clone https://github.com/aerdem4/lofo-importance
    
  • PyPi (πŸ“₯ 1.5K / month Β· πŸ“¦ 5 Β· ⏱️ 14.02.2025):

    pip install lofo-importance
    
</details> <details><summary><b><a href="https://github.com/parrt/random-forest-importances">random-forest-importances</a></b> (πŸ₯‰19 Β· ⭐ 620 Β· πŸ’€) - Code to compute permutation and drop-column.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 130 Β· πŸ“‹ 39 - 20% open Β· ⏱️ 24.03.2025):

    git clone https://github.com/parrt/random-forest-importances
    
  • PyPi (πŸ“₯ 16K / month Β· πŸ“¦ 5 Β· ⏱️ 28.01.2021):

    pip install rfpimp
    
</details> <details><summary><b><a href="https://github.com/tensorflow/fairness-indicators">fairness-indicators</a></b> (πŸ₯‰18 Β· ⭐ 360) - Tensorflows Fairness Evaluation and Visualization.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 39 Β· πŸ”€ 86 Β· πŸ“‹ 45 - 77% open Β· ⏱️ 04.08.2025):

    git clone https://github.com/tensorflow/fairness-indicators
    
  • PyPi (πŸ“₯ 1.1K / month Β· ⏱️ 25.06.2025):

    pip install fairness-indicators
    
</details> <details><summary>Show 32 hidden projects...</summary>
  • <b><a href="https://github.com/marcotcr/lime">Lime</a></b> (πŸ₯ˆ32 Β· ⭐ 12K Β· πŸ’€) - Lime: Explaining the predictions of any machine learning classifier. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code>
  • <b><a href="https://github.com/bmabey/pyLDAvis">pyLDAvis</a></b> (πŸ₯ˆ29 Β· ⭐ 1.8K Β· πŸ’€) - Python library for interactive topic model visualization... <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/DistrictDataLabs/yellowbrick">yellowbrick</a></b> (πŸ₯ˆ27 Β· ⭐ 4.4K Β· πŸ’€) - Visual analysis and diagnostic tools to facilitate.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/deepchecks/deepchecks">Deep Checks</a></b> (πŸ₯ˆ27 Β· ⭐ 3.9K) - Deepchecks: Tests for Continuous Validation of ML Models &.. <code><a href="http://bit.ly/3pwmjO5">❗️AGPL-3.0</a></code>
  • <b><a href="https://github.com/SeldonIO/alibi">Alibi</a></b> (πŸ₯ˆ27 Β· ⭐ 2.6K) - Algorithms for explaining machine learning models. <code><a href="https://tldrlegal.com/search?q=Intel">❗️Intel</a></code>
  • <b><a href="https://github.com/reiinakano/scikit-plot">scikit-plot</a></b> (πŸ₯ˆ27 Β· ⭐ 2.4K Β· πŸ’€) - An intuitive library to add plotting functionality to.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/ModelOriented/DALEX">DALEX</a></b> (πŸ₯ˆ27 Β· ⭐ 1.4K) - moDel Agnostic Language for Exploration and eXplanation (JMLR 2018;.. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code>
  • <b><a href="https://github.com/TeamHG-Memex/eli5">eli5</a></b> (πŸ₯ˆ26 Β· ⭐ 2.8K Β· πŸ’€) - A library for debugging/inspecting machine learning classifiers and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/albermax/innvestigate">iNNvestigate</a></b> (πŸ₯ˆ26 Β· ⭐ 1.3K Β· πŸ’€) - A toolbox to iNNvestigate neural networks predictions!. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/tensorflow/lucid">Lucid</a></b> (πŸ₯‰25 Β· ⭐ 4.7K Β· πŸ’€) - A collection of infrastructure and tools for research in.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/raghakot/keras-vis">keras-vis</a></b> (πŸ₯‰25 Β· ⭐ 3K Β· πŸ’€) - Neural network visualization toolkit for keras. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/mckinsey/causalnex">CausalNex</a></b> (πŸ₯‰24 Β· ⭐ 2.4K Β· πŸ’€) - A Python library that helps data scientists to infer.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/marcotcr/checklist">checklist</a></b> (πŸ₯‰24 Β· ⭐ 2K Β· πŸ’€) - Beyond Accuracy: Behavioral Testing of NLP models with CheckList. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/PAIR-code/what-if-tool">What-If Tool</a></b> (πŸ₯‰23 Β· ⭐ 980 Β· πŸ’€) - Source code/webpage/demos for the What-If Tool. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/sicara/tf-explain">tf-explain</a></b> (πŸ₯‰22 Β· ⭐ 1K Β· πŸ’€) - Interpretability Methods for tf.keras models with Tensorflow.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/kundajelab/deeplift">deeplift</a></b> (πŸ₯‰22 Β· ⭐ 870 Β· πŸ’€) - Public facing deeplift repo. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/andosa/treeinterpreter">TreeInterpreter</a></b> (πŸ₯‰22 Β· ⭐ 760 Β· πŸ’€) - Package for interpreting scikit-learns decision tree.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/understandable-machine-intelligence-lab/Quantus">Quantus</a></b> (πŸ₯‰22 Β· ⭐ 630) - Quantus is an eXplainable AI toolkit for responsible evaluation of.. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code>
  • <b><a href="https://github.com/EthicalML/xai">XAI</a></b> (πŸ₯‰21 Β· ⭐ 1.2K Β· πŸ’€) - XAI - An eXplainability toolbox for machine learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/tensorflow/tcav">tcav</a></b> (πŸ₯‰20 Β· ⭐ 640 Β· πŸ’€) - Code for the TCAV ML interpretability project. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/jalammar/ecco">ecco</a></b> (πŸ₯‰19 Β· ⭐ 2.1K Β· πŸ’€) - Explain, analyze, and visualize NLP language models. Ecco creates.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/edublancas/sklearn-evaluation">sklearn-evaluation</a></b> (πŸ₯‰17 Β· ⭐ 460 Β· πŸ’€) - Machine learning model evaluation made easy: plots,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/tensorflow/model-card-toolkit">model-card-toolkit</a></b> (πŸ₯‰17 Β· ⭐ 440 Β· πŸ’€) - A toolkit that streamlines and automates the.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/marcotcr/anchor">Anchor</a></b> (πŸ₯‰16 Β· ⭐ 810 Β· πŸ’€) - Code for High-Precision Model-Agnostic Explanations paper. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code>
  • <b><a href="https://github.com/MisaOgura/flashtorch">FlashTorch</a></b> (πŸ₯‰15 Β· ⭐ 740 Β· πŸ’€) - Visualization toolkit for neural networks in PyTorch! Demo --. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/explainX/explainx">ExplainX.ai</a></b> (πŸ₯‰15 Β· ⭐ 440 Β· πŸ’€) - Explainable AI framework for data scientists. Explain & debug any.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/givasile/effector">effector</a></b> (πŸ₯‰15 Β· ⭐ 120) - Effector - a Python package for global and regional effect methods. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/oracle/Skater">Skater</a></b> (πŸ₯‰14 Β· ⭐ 1.1K) - Python Library for Model Interpretation/Explanations. <code><a href="https://tldrlegal.com/search?q=UPL-1.0">❗️UPL-1.0</a></code>
  • <b><a href="https://github.com/interpretml/interpret-text">interpret-text</a></b> (πŸ₯‰14 Β· ⭐ 430 Β· πŸ’€) - A library that incorporates state-of-the-art explainers.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/intuit/bias-detector">bias-detector</a></b> (πŸ₯‰13 Β· ⭐ 45 Β· πŸ’€) - Bias Detector is a python package for detecting bias in machine.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/suinleelab/attributionpriors">Attribution Priors</a></b> (πŸ₯‰12 Β· ⭐ 120 Β· πŸ’€) - Tools for training explainable models using.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/SAP-archive/contextual-ai">contextual-ai</a></b> (πŸ₯‰12 Β· ⭐ 87 Β· πŸ’€) - Contextual AI adds explainability to different stages of.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
</details> <br>

Vector Similarity Search (ANN)

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarity Search.

πŸ”—Β <b><a href="https://github.com/erikbern/ann-benchmarks">ANN Benchmarks</a></b> ( ⭐ 5.5K) - Benchmarks of approximate nearest neighbor libraries in Python.

<details><summary><b><a href="https://github.com/milvus-io/milvus">Milvus</a></b> (πŸ₯‡43 Β· ⭐ 38K) - Milvus is a high-performance, cloud-native vector database built for.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 330 Β· πŸ”€ 3.5K Β· πŸ“₯ 290K Β· πŸ“‹ 15K - 5% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/milvus-io/milvus
    
  • PyPi (πŸ“₯ 3.3M / month Β· πŸ“¦ 350 Β· ⏱️ 19.09.2025):

    pip install pymilvus
    
  • Docker Hub (πŸ“₯ 72M Β· ⭐ 90 Β· ⏱️ 30.10.2025):

    docker pull milvusdb/milvus
    
</details> <details><summary><b><a href="https://github.com/facebookresearch/faiss">Faiss</a></b> (πŸ₯‡42 Β· ⭐ 38K Β· πŸ“ˆ) - A library for efficient similarity search and clustering of dense vectors. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 4K Β· πŸ“¦ 5K Β· πŸ“‹ 2.7K - 9% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/facebookresearch/faiss
    
  • PyPi (πŸ“₯ 3.3M / month Β· πŸ“¦ 350 Β· ⏱️ 19.09.2025):

    pip install pymilvus
    
  • Conda (πŸ“₯ 3M Β· ⏱️ 22.04.2025):

    conda install -c conda-forge faiss
    
</details> <details><summary><b><a href="https://github.com/spotify/annoy">Annoy</a></b> (πŸ₯ˆ35 Β· ⭐ 14K) - Approximate Nearest Neighbors in C++/Python optimized for memory usage.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 90 Β· πŸ”€ 1.2K Β· πŸ“¦ 5.4K Β· πŸ“‹ 420 - 16% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/spotify/annoy
    
  • PyPi (πŸ“₯ 1M / month Β· πŸ“¦ 200 Β· ⏱️ 14.06.2023):

    pip install annoy
    
  • Conda (πŸ“₯ 800K Β· ⏱️ 01.09.2025):

    conda install -c conda-forge python-annoy
    
</details> <details><summary><b><a href="https://github.com/unum-cloud/USearch">USearch</a></b> (πŸ₯ˆ33 Β· ⭐ 3.2K) - Fast Open-Source Search & Clustering engine for Vectors & Arbitrary.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 81 Β· πŸ”€ 230 Β· πŸ“₯ 110K Β· πŸ“¦ 210 Β· πŸ“‹ 250 - 32% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/unum-cloud/usearch
    
  • PyPi (πŸ“₯ 140K / month Β· πŸ“¦ 44 Β· ⏱️ 04.09.2025):

    pip install usearch
    
  • npm (πŸ“₯ 18K / month Β· πŸ“¦ 23 Β· ⏱️ 29.10.2025):

    npm install usearch
    
  • Docker Hub (πŸ“₯ 480 Β· ⭐ 1 Β· ⏱️ 29.10.2025):

    docker pull unum/usearch
    
</details> <details><summary><b><a href="https://github.com/nmslib/nmslib">NMSLIB</a></b> (πŸ₯ˆ32 Β· ⭐ 3.5K) - Non-Metric Space Library (NMSLIB): An efficient similarity search.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 49 Β· πŸ”€ 460 Β· πŸ“¦ 1.4K Β· πŸ“‹ 440 - 20% open Β· ⏱️ 22.10.2025):

    git clone https://github.com/nmslib/nmslib
    
  • PyPi (πŸ“₯ 280K / month Β· πŸ“¦ 67 Β· ⏱️ 23.10.2025):

    pip install nmslib
    
  • Conda (πŸ“₯ 230K Β· ⏱️ 30.08.2025):

    conda install -c conda-forge nmslib
    
</details> <details><summary><b><a href="https://github.com/lmcinnes/pynndescent">PyNNDescent</a></b> (πŸ₯‰28 Β· ⭐ 950) - A Python nearest neighbor descent for approximate nearest neighbors. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 110 Β· πŸ“¦ 13K Β· πŸ“‹ 140 - 53% open Β· ⏱️ 17.10.2025):

    git clone https://github.com/lmcinnes/pynndescent
    
  • PyPi (πŸ“₯ 2.5M / month Β· πŸ“¦ 160 Β· ⏱️ 17.06.2024):

    pip install pynndescent
    
  • Conda (πŸ“₯ 2.5M Β· ⏱️ 22.04.2025):

    conda install -c conda-forge pynndescent
    
</details> <details><summary><b><a href="https://github.com/yahoojapan/NGT">NGT</a></b> (πŸ₯‰22 Β· ⭐ 1.3K) - Nearest Neighbor Search with Neighborhood Graph and Tree for High-.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 120 Β· πŸ“‹ 150 - 18% open Β· ⏱️ 15.10.2025):

    git clone https://github.com/yahoojapan/NGT
    
  • PyPi (πŸ“₯ 1.8K / month Β· πŸ“¦ 12 Β· ⏱️ 26.02.2025):

    pip install ngt
    
</details> <details><summary>Show 5 hidden projects...</summary>
  • <b><a href="https://github.com/nmslib/hnswlib">hnswlib</a></b> (πŸ₯ˆ32 Β· ⭐ 5K Β· πŸ’€) - Header-only C++/python library for fast approximate nearest.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/pixelogik/NearPy">NearPy</a></b> (πŸ₯‰22 Β· ⭐ 770 Β· πŸ’€) - Python framework for fast (approximated) nearest neighbour search in.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/kakao/n2">N2</a></b> (πŸ₯‰22 Β· ⭐ 580 Β· πŸ’€) - TOROS N2 - lightweight approximate Nearest Neighbor library which runs.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/plasticityai/magnitude">Magnitude</a></b> (πŸ₯‰20 Β· ⭐ 1.7K Β· πŸ’€) - A fast, efficient universal vector embedding utility package. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/facebookresearch/pysparnn">PySparNN</a></b> (πŸ₯‰11 Β· ⭐ 920 Β· πŸ’€) - Approximate Nearest Neighbor Search for Sparse Data in Python!. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
</details> <br>

Probabilistics & Statistics

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries providing capabilities for probabilistic programming/reasoning, bayesian inference, gaussian processes, or statistics.

<details><summary><b><a href="https://github.com/pymc-devs/pymc">PyMC3</a></b> (πŸ₯‡40 Β· ⭐ 9.3K) - Bayesian Modeling and Probabilistic Programming in Python. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 530 Β· πŸ”€ 2.1K Β· πŸ“₯ 140 Β· πŸ“¦ 7.7K Β· πŸ“‹ 3.6K - 11% open Β· ⏱️ 28.10.2025):

    git clone https://github.com/pymc-devs/pymc
    
  • PyPi (πŸ“₯ 330K / month Β· πŸ“¦ 190 Β· ⏱️ 31.05.2024):

    pip install pymc3
    
  • Conda (πŸ“₯ 860K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge pymc3
    
</details> <details><summary><b><a href="https://github.com/tensorflow/probability">tensorflow-probability</a></b> (πŸ₯‡35 Β· ⭐ 4.4K) - Probabilistic reasoning and statistical analysis in.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 500 Β· πŸ”€ 1.1K Β· πŸ“¦ 4 Β· πŸ“‹ 1.5K - 48% open Β· ⏱️ 22.10.2025):

    git clone https://github.com/tensorflow/probability
    
  • PyPi (πŸ“₯ 880K / month Β· πŸ“¦ 620 Β· ⏱️ 08.11.2024):

    pip install tensorflow-probability
    
  • Conda (πŸ“₯ 200K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge tensorflow-probability
    
</details> <details><summary><b><a href="https://github.com/cornellius-gp/gpytorch">GPyTorch</a></b> (πŸ₯‡34 Β· ⭐ 3.8K) - A highly efficient implementation of Gaussian Processes in PyTorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 580 Β· πŸ“¦ 3.2K Β· πŸ“‹ 1.4K - 28% open Β· ⏱️ 14.10.2025):

    git clone https://github.com/cornellius-gp/gpytorch
    
  • PyPi (πŸ“₯ 500K / month Β· πŸ“¦ 250 Β· ⏱️ 14.10.2025):

    pip install gpytorch
    
  • Conda (πŸ“₯ 230K Β· ⏱️ 18.10.2025):

    conda install -c conda-forge gpytorch
    
</details> <details><summary><b><a href="https://github.com/pgmpy/pgmpy">pgmpy</a></b> (πŸ₯‡34 Β· ⭐ 3.1K) - Python library for causal inference and probabilistic modeling. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 180 Β· πŸ”€ 860 Β· πŸ“₯ 680 Β· πŸ“¦ 1.7K Β· πŸ“‹ 1.1K - 27% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/pgmpy/pgmpy
    
  • PyPi (πŸ“₯ 120K / month Β· πŸ“¦ 72 Β· ⏱️ 31.03.2025):

    pip install pgmpy
    
</details> <details><summary><b><a href="https://github.com/pydata/patsy">patsy</a></b> (πŸ₯‡34 Β· ⭐ 980) - Describing statistical models in Python using symbolic formulas. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 100 Β· πŸ“¦ 130K Β· πŸ“‹ 160 - 46% open Β· ⏱️ 20.10.2025):

    git clone https://github.com/pydata/patsy
    
  • PyPi (πŸ“₯ 22M / month Β· πŸ“¦ 680 Β· ⏱️ 20.10.2025):

    pip install patsy
    
  • Conda (πŸ“₯ 19M Β· ⏱️ 20.10.2025):

    conda install -c conda-forge patsy
    
</details> <details><summary><b><a href="https://github.com/pyro-ppl/pyro">Pyro</a></b> (πŸ₯ˆ32 Β· ⭐ 8.9K) - Deep universal probabilistic programming with Python and PyTorch. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 160 Β· πŸ”€ 1K Β· πŸ“‹ 1.1K - 24% open Β· ⏱️ 09.07.2025):

    git clone https://github.com/pyro-ppl/pyro
    
  • PyPi (πŸ“₯ 630K / month Β· πŸ“¦ 190 Β· ⏱️ 02.06.2024):

    pip install pyro-ppl
    
  • Conda (πŸ“₯ 280K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge pyro-ppl
    
</details> <details><summary><b><a href="https://github.com/SALib/SALib">SALib</a></b> (πŸ₯ˆ31 Β· ⭐ 960) - Sensitivity Analysis Library in Python. Contains Sobol, Morris, FAST, and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 54 Β· πŸ”€ 250 Β· πŸ“¦ 1.6K Β· πŸ“‹ 350 - 18% open Β· ⏱️ 12.10.2025):

    git clone https://github.com/SALib/SALib
    
  • PyPi (πŸ“₯ 250K / month Β· πŸ“¦ 190 Β· ⏱️ 12.10.2025):

    pip install salib
    
  • Conda (πŸ“₯ 290K Β· ⏱️ 12.10.2025):

    conda install -c conda-forge salib
    
</details> <details><summary><b><a href="https://github.com/hmmlearn/hmmlearn">hmmlearn</a></b> (πŸ₯ˆ30 Β· ⭐ 3.3K Β· πŸ’€) - Hidden Markov Models in Python, with scikit-learn like API. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 49 Β· πŸ”€ 740 Β· πŸ“¦ 3.7K Β· πŸ“‹ 450 - 16% open Β· ⏱️ 31.10.2024):

    git clone https://github.com/hmmlearn/hmmlearn
    
  • PyPi (πŸ“₯ 240K / month Β· πŸ“¦ 92 Β· ⏱️ 31.10.2024):

    pip install hmmlearn
    
  • Conda (πŸ“₯ 430K Β· ⏱️ 10.09.2025):

    conda install -c conda-forge hmmlearn
    
</details> <details><summary><b><a href="https://github.com/dfm/emcee">emcee</a></b> (πŸ₯ˆ30 Β· ⭐ 1.5K) - The Python ensemble sampling toolkit for affine-invariant MCMC. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 76 Β· πŸ”€ 430 Β· πŸ“¦ 3.2K Β· πŸ“‹ 300 - 19% open Β· ⏱️ 14.10.2025):

    git clone https://github.com/dfm/emcee
    
  • PyPi (πŸ“₯ 170K / month Β· πŸ“¦ 440 Β· ⏱️ 19.04.2024):

    pip install emcee
    
  • Conda (πŸ“₯ 510K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge emcee
    
</details> <details><summary><b><a href="https://github.com/GPflow/GPflow">GPflow</a></b> (πŸ₯‰29 Β· ⭐ 1.9K) - Gaussian processes in TensorFlow. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 84 Β· πŸ”€ 430 Β· πŸ“¦ 790 Β· πŸ“‹ 840 - 19% open Β· ⏱️ 29.05.2025):

    git clone https://github.com/GPflow/GPflow
    
  • PyPi (πŸ“₯ 32K / month Β· πŸ“¦ 43 Β· ⏱️ 29.05.2025):

    pip install gpflow
    
  • Conda (πŸ“₯ 51K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge gpflow
    
</details> <details><summary><b><a href="https://github.com/bambinos/bambi">bambi</a></b> (πŸ₯‰29 Β· ⭐ 1.2K) - BAyesian Model-Building Interface (Bambi) in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 47 Β· πŸ”€ 140 Β· πŸ“¦ 220 Β· πŸ“‹ 460 - 21% open Β· ⏱️ 24.10.2025):

    git clone https://github.com/bambinos/bambi
    
  • PyPi (πŸ“₯ 48K / month Β· πŸ“¦ 19 Β· ⏱️ 24.10.2025):

    pip install bambi
    
  • Conda (πŸ“₯ 56K Β· ⏱️ 27.10.2025):

    conda install -c conda-forge bambi
    
</details> <details><summary><b><a href="https://github.com/jmschrei/pomegranate">pomegranate</a></b> (πŸ₯‰26 Β· ⭐ 3.5K Β· πŸ’€) - Fast, flexible and easy to use probabilistic modelling in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 75 Β· πŸ”€ 590 Β· πŸ“‹ 800 - 4% open Β· ⏱️ 07.02.2025):

    git clone https://github.com/jmschrei/pomegranate
    
  • PyPi (πŸ“₯ 36K / month Β· πŸ“¦ 67 Β· ⏱️ 07.02.2025):

    pip install pomegranate
    
  • Conda (πŸ“₯ 230K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge pomegranate
    
</details> <details><summary><b><a href="https://github.com/maximtrp/scikit-posthocs">scikit-posthocs</a></b> (πŸ₯‰24 Β· ⭐ 380) - Multiple Pairwise Comparisons (Post Hoc) Tests in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 41 Β· πŸ“₯ 67 Β· πŸ“¦ 1.2K Β· πŸ“‹ 72 - 6% open Β· ⏱️ 11.09.2025):

    git clone https://github.com/maximtrp/scikit-posthocs
    
  • PyPi (πŸ“₯ 120K / month Β· πŸ“¦ 73 Β· ⏱️ 29.03.2025):

    pip install scikit-posthocs
    
  • Conda (πŸ“₯ 1.1M Β· ⏱️ 22.04.2025):

    conda install -c conda-forge scikit-posthocs
    
</details> <details><summary><b><a href="https://github.com/twopirllc/pandas-ta">pandas-ta</a></b> (πŸ₯‰23 Β· ⭐ 5.5K) - Technical Analysis Indicators - Pandas TA is an easy to use.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 40 Β· πŸ”€ 1.1K):

    git clone https://github.com/twopirllc/pandas-ta
    
  • PyPi (πŸ“₯ 290K / month Β· πŸ“¦ 190 Β· ⏱️ 14.09.2025):

    pip install pandas-ta
    
  • Conda (πŸ“₯ 39K Β· ⏱️ 23.09.2025):

    conda install -c conda-forge pandas-ta
    
</details> <details><summary><b><a href="https://github.com/baal-org/baal">Baal</a></b> (πŸ₯‰22 Β· ⭐ 910) - Bayesian active learning library for research and industrial usecases. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 87 Β· πŸ“¦ 67 Β· πŸ“‹ 120 - 18% open Β· ⏱️ 07.10.2025):

    git clone https://github.com/baal-org/baal
    
  • PyPi (πŸ“₯ 1.8K / month Β· πŸ“¦ 2 Β· ⏱️ 24.06.2025):

    pip install baal
    
  • Conda (πŸ“₯ 15K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge baal
    
</details> <details><summary><b><a href="https://github.com/uber/orbit">Orbit</a></b> (πŸ₯‰21 Β· ⭐ 2K) - A Python package for Bayesian forecasting with object-oriented design.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 21 Β· πŸ”€ 140 Β· πŸ“‹ 410 - 13% open Β· ⏱️ 05.06.2025):

    git clone https://github.com/uber/orbit
    
  • PyPi (πŸ“₯ 24K / month Β· πŸ“¦ 1 Β· ⏱️ 01.04.2024):

    pip install orbit-ml
    
</details> <details><summary><b><a href="https://github.com/mattjj/pyhsmm">pyhsmm</a></b> (πŸ₯‰21 Β· ⭐ 570 Β· πŸ’€) - Bayesian inference in HSMMs and HMMs. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 14 Β· πŸ”€ 170 Β· πŸ“¦ 35 Β· πŸ“‹ 100 - 39% open Β· ⏱️ 25.01.2025):

    git clone https://github.com/mattjj/pyhsmm
    
  • PyPi (πŸ“₯ 300 / month Β· πŸ“¦ 1 Β· ⏱️ 10.05.2017):

    pip install pyhsmm
    
</details> <details><summary><b><a href="https://github.com/ENSTA-U2IS-AI/torch-uncertainty">TorchUncertainty</a></b> (πŸ₯‰20 Β· ⭐ 440 Β· πŸ“‰) - Open-source framework for uncertainty and deep.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 13 Β· πŸ”€ 35 Β· πŸ“‹ 67 - 23% open Β· ⏱️ 31.07.2025):

    git clone https://github.com/ENSTA-U2IS-AI/torch-uncertainty
    
  • PyPi (πŸ“₯ 920 / month Β· πŸ“¦ 4 Β· ⏱️ 31.07.2025):

    pip install torch-uncertainty
    
</details> <details><summary>Show 6 hidden projects...</summary>
  • <b><a href="https://github.com/rlabbe/filterpy">filterpy</a></b> (πŸ₯ˆ31 Β· ⭐ 3.7K Β· πŸ’€) - Python Kalman filtering and optimal estimation library. Implements.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/raphaelvallat/pingouin">pingouin</a></b> (πŸ₯‰29 Β· ⭐ 1.8K) - Statistical package in Python based on Pandas. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code>
  • <b><a href="https://github.com/blei-lab/edward">Edward</a></b> (πŸ₯‰27 Β· ⭐ 4.8K Β· πŸ’€) - A probabilistic programming language in TensorFlow. Deep.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/stan-dev/pystan">PyStan</a></b> (πŸ₯‰27 Β· ⭐ 360 Β· πŸ’€) - PyStan, a Python interface to Stan, a platform for statistical.. <code><a href="http://bit.ly/3hkKRql">ISC</a></code>
  • <b><a href="https://github.com/pyro-ppl/funsor">Funsor</a></b> (πŸ₯‰21 Β· ⭐ 240 Β· πŸ’€) - Functional tensors for probabilistic programming. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/thu-ml/zhusuan">ZhuSuan</a></b> (πŸ₯‰15 Β· ⭐ 2.2K Β· πŸ’€) - A probabilistic programming library for Bayesian deep learning,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
</details> <br>

Adversarial Robustness

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries for testing the robustness of machine learning models against attacks with adversarial/malicious examples.

<details><summary><b><a href="https://github.com/Trusted-AI/adversarial-robustness-toolbox">ART</a></b> (πŸ₯‡34 Β· ⭐ 5.6K) - Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.2K Β· πŸ“¦ 770 Β· πŸ“‹ 910 - 1% open Β· ⏱️ 17.10.2025):

    git clone https://github.com/Trusted-AI/adversarial-robustness-toolbox
    
  • PyPi (πŸ“₯ 29K / month Β· πŸ“¦ 25 Β· ⏱️ 07.07.2025):

    pip install adversarial-robustness-toolbox
    
  • Conda (πŸ“₯ 85K Β· ⏱️ 07.07.2025):

    conda install -c conda-forge adversarial-robustness-toolbox
    
</details> <details><summary><b><a href="https://github.com/QData/TextAttack">TextAttack</a></b> (πŸ₯ˆ28 Β· ⭐ 3.3K) - TextAttack is a Python framework for adversarial attacks, data.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 67 Β· πŸ”€ 420 Β· πŸ“¦ 430 Β· πŸ“‹ 290 - 23% open Β· ⏱️ 10.07.2025):

    git clone https://github.com/QData/TextAttack
    
  • PyPi (πŸ“₯ 9.1K / month Β· πŸ“¦ 11 Β· ⏱️ 11.03.2024):

    pip install textattack
    
  • Conda (πŸ“₯ 11K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge textattack
    
</details> <details><summary>Show 7 hidden projects...</summary>
  • <b><a href="https://github.com/cleverhans-lab/cleverhans">CleverHans</a></b> (πŸ₯ˆ29 Β· ⭐ 6.4K Β· πŸ’€) - An adversarial example library for constructing attacks,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/bethgelab/foolbox">Foolbox</a></b> (πŸ₯ˆ28 Β· ⭐ 2.9K Β· πŸ’€) - A Python toolbox to create adversarial examples that fool neural.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/BorealisAI/advertorch">advertorch</a></b> (πŸ₯‰24 Β· ⭐ 1.4K Β· πŸ’€) - A Toolbox for Adversarial Robustness Research. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/MadryLab/robustness">robustness</a></b> (πŸ₯‰20 Β· ⭐ 950 Β· πŸ’€) - A library for experimenting with, training and evaluating neural.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/advboxes/AdvBox">AdvBox</a></b> (πŸ₯‰19 Β· ⭐ 1.4K Β· πŸ’€) - Advbox is a toolbox to generate adversarial examples that fool.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/textflint/textflint">textflint</a></b> (πŸ₯‰17 Β· ⭐ 650 Β· πŸ’€) - Unified Multilingual Robustness Evaluation Toolkit for.. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code>
  • <b><a href="https://github.com/airbnb/artificial-adversary">Adversary</a></b> (πŸ₯‰15 Β· ⭐ 400 Β· πŸ’€) - Tool to generate adversarial text examples and test machine.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
</details> <br>

GPU & Accelerator Utilities

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries that require and make use of CUDA/GPU or other accelerator hardware capabilities to optimize machine learning tasks.

<details><summary><b><a href="https://github.com/huggingface/optimum">optimum</a></b> (πŸ₯‡37 Β· ⭐ 3.1K) - Accelerate inference and training of Transformers, Diffusers, TIMM.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 150 Β· πŸ”€ 600 Β· πŸ“¦ 6.3K Β· πŸ“‹ 860 - 30% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/huggingface/optimum
    
  • PyPi (πŸ“₯ 3.7M / month Β· πŸ“¦ 270 Β· ⏱️ 09.10.2025):

    pip install optimum
    
  • Conda (πŸ“₯ 50K Β· ⏱️ 09.10.2025):

    conda install -c conda-forge optimum
    
</details> <details><summary><b><a href="https://github.com/rapidsai/cudf">cuDF</a></b> (πŸ₯‡35 Β· ⭐ 9.3K) - cuDF - GPU DataFrame Library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 310 Β· πŸ”€ 980 Β· πŸ“¦ 64 Β· πŸ“‹ 7.3K - 15% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/rapidsai/cudf
    
  • PyPi (πŸ“₯ 2.8K / month Β· πŸ“¦ 22 Β· ⏱️ 01.06.2020):

    pip install cudf
    
</details> <details><summary><b><a href="https://github.com/inducer/pycuda">PyCUDA</a></b> (πŸ₯ˆ33 Β· ⭐ 2K) - CUDA integration for Python, plus shiny features. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 83 Β· πŸ”€ 300 Β· πŸ“¦ 4K Β· πŸ“‹ 290 - 29% open Β· ⏱️ 12.10.2025):

    git clone https://github.com/inducer/pycuda
    
  • PyPi (πŸ“₯ 66K / month Β· πŸ“¦ 200 Β· ⏱️ 09.09.2025):

    pip install pycuda
    
  • Conda (πŸ“₯ 1.1M Β· ⏱️ 27.10.2025):

    conda install -c conda-forge pycuda
    
</details> <details><summary><b><a href="https://github.com/NVIDIA/apex">Apex</a></b> (πŸ₯ˆ32 Β· ⭐ 8.8K) - A PyTorch Extension: Tools for easy mixed precision and distributed.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 140 Β· πŸ”€ 1.4K Β· πŸ“¦ 3.3K Β· πŸ“‹ 1.3K - 57% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/NVIDIA/apex
    
  • Conda (πŸ“₯ 580K Β· ⏱️ 26.07.2025):

    conda install -c conda-forge nvidia-apex
    
</details> <details><summary><b><a href="https://github.com/rapidsai/cuml">cuML</a></b> (πŸ₯ˆ31 Β· ⭐ 5K) - cuML - RAPIDS Machine Learning Library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 600 Β· πŸ“‹ 3K - 31% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/rapidsai/cuml
    
  • PyPi (πŸ“₯ 2.5K / month Β· πŸ“¦ 14 Β· ⏱️ 01.06.2020):

    pip install cuml
    
</details> <details><summary><b><a href="https://github.com/wookayin/gpustat">gpustat</a></b> (πŸ₯ˆ29 Β· ⭐ 4.3K) - A simple command-line utility for querying and monitoring GPU status. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 280 Β· πŸ“¦ 7.9K Β· πŸ“‹ 130 - 22% open Β· ⏱️ 13.04.2025):

    git clone https://github.com/wookayin/gpustat
    
  • PyPi (πŸ“₯ 1.1M / month Β· πŸ“¦ 150 Β· ⏱️ 22.08.2023):

    pip install gpustat
    
  • Conda (πŸ“₯ 310K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge gpustat
    
</details> <details><summary><b><a href="https://github.com/arrayfire/arrayfire">ArrayFire</a></b> (πŸ₯ˆ28 Β· ⭐ 4.8K) - ArrayFire: a general purpose GPU library. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 97 Β· πŸ”€ 540 Β· πŸ“₯ 9.6K Β· πŸ“‹ 1.8K - 19% open Β· ⏱️ 28.07.2025):

    git clone https://github.com/arrayfire/arrayfire
    
  • PyPi (πŸ“₯ 4.5K / month Β· πŸ“¦ 13 Β· ⏱️ 22.02.2022):

    pip install arrayfire
    
</details> <details><summary><b><a href="https://github.com/rapidsai/cugraph">cuGraph</a></b> (πŸ₯ˆ28 Β· ⭐ 2.1K) - cuGraph - RAPIDS Graph Analytics Library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 340 Β· πŸ“‹ 1.9K - 6% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/rapidsai/cugraph
    
  • PyPi (πŸ“₯ 550 / month Β· πŸ“¦ 4 Β· ⏱️ 01.06.2020):

    pip install cugraph
    
  • Conda (πŸ“₯ 69K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge libcugraph
    
</details> <details><summary><b><a href="https://github.com/cupy/cupy">CuPy</a></b> (πŸ₯‰27 Β· ⭐ 11K) - NumPy & SciPy for GPU. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 340 Β· πŸ”€ 950):

    git clone https://github.com/cupy/cupy
    
  • PyPi (πŸ“₯ 39K / month Β· πŸ“¦ 400 Β· ⏱️ 18.08.2025):

    pip install cupy
    
  • Conda (πŸ“₯ 7.2M Β· ⏱️ 14.09.2025):

    conda install -c conda-forge cupy
    
  • Docker Hub (πŸ“₯ 92K Β· ⭐ 14 Β· ⏱️ 18.08.2025):

    docker pull cupy/cupy
    
</details> <details><summary><b><a href="https://github.com/NVIDIA/DALI">DALI</a></b> (πŸ₯‰25 Β· ⭐ 5.5K) - A GPU-accelerated library containing highly optimized building blocks.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 99 Β· πŸ”€ 650 Β· πŸ“‹ 1.7K - 15% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/NVIDIA/DALI
    
</details> <details><summary><b><a href="https://github.com/KomputeProject/kompute">Vulkan Kompute</a></b> (πŸ₯‰23 Β· ⭐ 2.4K) - General purpose GPU compute framework built on Vulkan to.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 35 Β· πŸ”€ 160 Β· πŸ“₯ 700 Β· πŸ“‹ 230 - 32% open Β· ⏱️ 05.10.2025):

    git clone https://github.com/KomputeProject/kompute
    
  • PyPi (πŸ“₯ 1.8K / month Β· ⏱️ 20.01.2024):

    pip install kp
    
</details> <details><summary>Show 9 hidden projects...</summary>
  • <b><a href="https://github.com/anderskm/gputil">GPUtil</a></b> (πŸ₯‰25 Β· ⭐ 1.2K Β· πŸ’€) - A Python module for getting the GPU status from NVIDA GPUs using.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/lebedov/scikit-cuda">scikit-cuda</a></b> (πŸ₯‰25 Β· ⭐ 990 Β· πŸ’€) - Python interface to GPU-powered libraries. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/fbcotter/py3nvml">py3nvml</a></b> (πŸ₯‰22 Β· ⭐ 250 Β· πŸ’€) - Python 3 Bindings for NVML library. Get NVIDIA GPU status inside.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/BlazingDB/blazingsql">BlazingSQL</a></b> (πŸ₯‰20 Β· ⭐ 2K Β· πŸ’€) - BlazingSQL is a lightweight, GPU accelerated, SQL engine for.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/NVIDIA-Merlin/Merlin">Merlin</a></b> (πŸ₯‰20 Β· ⭐ 860 Β· πŸ’€) - NVIDIA Merlin is an open source library providing end-to-end GPU-.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
  • <b><a href="https://github.com/nicolargo/nvidia-ml-py3">nvidia-ml-py3</a></b> (πŸ₯‰18 Β· ⭐ 140 Β· πŸ’€) - Python 3 Bindings for the NVIDIA Management Library. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
  • <b><a href="https://github.com/Santosh-Gupta/SpeedTorch">SpeedTorch</a></b> (πŸ₯‰15 Β· ⭐ 680 Β· πŸ’€) - Library for faster pinned CPU - GPU transfer in Pytorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/stas00/ipyexperiments">ipyexperiments</a></b> (πŸ₯‰15 Β· ⭐ 220 Β· πŸ’€) - Automatic GPU+CPU memory profiling, re-use and memory.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/rapidsai/cusignal">cuSignal</a></b> (πŸ₯‰14 Β· ⭐ 730 Β· πŸ’€) - GPU accelerated signal processing. <code>❗Unlicensed</code>
</details> <br>

Tensorflow Utilities

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries that extend TensorFlow with additional capabilities.

<details><summary><b><a href="https://github.com/tensorflow/datasets">TensorFlow Datasets</a></b> (πŸ₯‡39 Β· ⭐ 4.5K) - TFDS is a collection of datasets ready to use with.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 660 Β· πŸ”€ 1.6K Β· πŸ“¦ 25K Β· πŸ“‹ 1.5K - 47% open Β· ⏱️ 17.10.2025):

    git clone https://github.com/tensorflow/datasets
    
  • PyPi (πŸ“₯ 1.8M / month Β· πŸ“¦ 340 Β· ⏱️ 28.05.2025):

    pip install tensorflow-datasets
    
  • Conda (πŸ“₯ 51K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge tensorflow-datasets
    
</details> <details><summary><b><a href="https://github.com/tensorflow/hub">tensorflow-hub</a></b> (πŸ₯ˆ31 Β· ⭐ 3.5K Β· πŸ’€) - A library for transfer learning by reusing parts of.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 1.7K Β· πŸ“‹ 710 - 2% open Β· ⏱️ 17.01.2025):

    git clone https://github.com/tensorflow/hub
    
  • PyPi (πŸ“₯ 2M / month Β· πŸ“¦ 300 Β· ⏱️ 30.01.2024):

    pip install tensorflow-hub
    
  • Conda (πŸ“₯ 130K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge tensorflow-hub
    
</details> <details><summary><b><a href="https://github.com/tensorflow/tfx">TFX</a></b> (πŸ₯ˆ31 Β· ⭐ 2.2K Β· πŸ’€) - TFX is an end-to-end platform for deploying production ML.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 200 Β· πŸ”€ 710 Β· πŸ“¦ 1.8K Β· πŸ“‹ 1.2K - 22% open Β· ⏱️ 26.03.2025):

    git clone https://github.com/tensorflow/tfx
    
  • PyPi (πŸ“₯ 37K / month Β· πŸ“¦ 17 Β· ⏱️ 11.12.2024):

    pip install tfx
    
</details> <details><summary><b><a href="https://github.com/tensorflow/model-optimization">TF Model Optimization</a></b> (πŸ₯ˆ29 Β· ⭐ 1.6K) - A toolkit to optimize ML models for deployment for.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 87 Β· πŸ”€ 320 Β· πŸ“‹ 400 - 57% open Β· ⏱️ 07.07.2025):

    git clone https://github.com/tensorflow/model-optimization
    
  • PyPi (πŸ“₯ 920K / month Β· πŸ“¦ 45 Β· ⏱️ 08.02.2024):

    pip install tensorflow-model-optimization
    
</details> <details><summary><b><a href="https://github.com/tensorflow/io">TensorFlow I/O</a></b> (πŸ₯ˆ29 Β· ⭐ 730) - Dataset, streaming, and file system extensions.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 120 Β· πŸ”€ 290 Β· πŸ“‹ 660 - 44% open Β· ⏱️ 10.04.2025):

    git clone https://github.com/tensorflow/io
    
  • PyPi (πŸ“₯ 730K / month Β· πŸ“¦ 61 Β· ⏱️ 01.07.2024):

    pip install tensorflow-io
    
</details> <details><summary><b><a href="https://github.com/tensorflow/transform">TensorFlow Transform</a></b> (πŸ₯‰26 Β· ⭐ 990) - Input pipeline framework. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 31 Β· πŸ”€ 220 Β· πŸ“‹ 220 - 17% open Β· ⏱️ 06.08.2025):

    git clone https://github.com/tensorflow/transform
    
  • PyPi (πŸ“₯ 250K / month Β· πŸ“¦ 19 Β· ⏱️ 13.06.2025):

    pip install tensorflow-transform
    
</details> <details><summary><b><a href="https://github.com/tensorflow/neural-structured-learning">Neural Structured Learning</a></b> (πŸ₯‰24 Β· ⭐ 1K Β· πŸ’€) - Training neural models with structured signals. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 39 Β· πŸ”€ 190 Β· πŸ“¦ 520 Β· πŸ“‹ 69 - 1% open Β· ⏱️ 29.01.2025):

    git clone https://github.com/tensorflow/neural-structured-learning
    
  • PyPi (πŸ“₯ 3.2K / month Β· πŸ“¦ 3 Β· ⏱️ 29.07.2022):

    pip install neural-structured-learning
    
</details> <details><summary><b><a href="https://github.com/tensorflow/cloud">TensorFlow Cloud</a></b> (πŸ₯‰21 Β· ⭐ 380) - The TensorFlow Cloud repository provides APIs that.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 29 Β· πŸ”€ 92 Β· πŸ“‹ 100 - 73% open Β· ⏱️ 01.10.2025):

    git clone https://github.com/tensorflow/cloud
    
  • PyPi (πŸ“₯ 18K / month Β· πŸ“¦ 7 Β· ⏱️ 17.06.2021):

    pip install tensorflow-cloud
    
</details> <details><summary><b><a href="https://github.com/tensorflow/compression">TF Compression</a></b> (πŸ₯‰20 Β· ⭐ 900) - Data compression in TensorFlow. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 260 Β· πŸ“‹ 100 - 10% open Β· ⏱️ 19.08.2025):

    git clone https://github.com/tensorflow/compression
    
  • PyPi (πŸ“₯ 4.3K / month Β· πŸ“¦ 2 Β· ⏱️ 02.02.2024):

    pip install tensorflow-compression
    
</details> <details><summary>Show 7 hidden projects...</summary>
  • <b><a href="https://github.com/tensorflow/tensor2tensor">tensor2tensor</a></b> (πŸ₯‡33 Β· ⭐ 17K Β· πŸ’€) - Library of deep learning models and datasets designed.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/tensorflow/addons">TF Addons</a></b> (πŸ₯ˆ32 Β· ⭐ 1.7K Β· πŸ’€) - Useful extra functionality for TensorFlow 2.x maintained.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/keras-team/keras-preprocessing">Keras-Preprocessing</a></b> (πŸ₯‰28 Β· ⭐ 1K Β· πŸ’€) - Utilities for working with image data, text data, and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/qubvel/efficientnet">efficientnet</a></b> (πŸ₯‰26 Β· ⭐ 2.1K Β· πŸ’€) - Implementation of EfficientNet model. Keras and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/PAIR-code/saliency">Saliency</a></b> (πŸ₯‰22 Β· ⭐ 980 Β· πŸ’€) - Framework-agnostic implementation for state-of-the-art.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/taehoonlee/tensornets">TensorNets</a></b> (πŸ₯‰21 Β· ⭐ 1K Β· πŸ’€) - High level network definitions with pre-trained weights in.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/geffy/tffm">tffm</a></b> (πŸ₯‰18 Β· ⭐ 780 Β· πŸ’€) - TensorFlow implementation of an arbitrary order Factorization Machine. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
</details> <br>

Jax Utilities

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries that extend Jax with additional capabilities.

<details><summary><b><a href="https://github.com/patrick-kidger/equinox">equinox</a></b> (πŸ₯‡33 Β· ⭐ 2.6K) - Elegant easy-to-use neural networks + scientific computing in.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 81 Β· πŸ”€ 170 Β· πŸ“¦ 1.4K Β· πŸ“‹ 610 - 35% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/patrick-kidger/equinox
    
  • PyPi (πŸ“₯ 500K / month Β· πŸ“¦ 350 Β· ⏱️ 09.10.2025):

    pip install equinox
    
</details> <details><summary>Show 2 hidden projects...</summary>
  • <b><a href="https://github.com/google/evojax">evojax</a></b> (πŸ₯‰18 Β· ⭐ 920 Β· πŸ’€) - EvoJAX: Hardware-accelerated Neuroevolution. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/ucl-bug/jaxdf">jaxdf</a></b> (πŸ₯‰12 Β· ⭐ 130 Β· πŸ’€) - A JAX-based research framework for writing differentiable.. <code><a href="http://bit.ly/37RvQcA">❗️LGPL-3.0</a></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code>
</details> <br>

Sklearn Utilities

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries that extend scikit-learn with additional capabilities.

<details><summary><b><a href="https://github.com/uxlfoundation/scikit-learn-intelex">scikit-learn-intelex</a></b> (πŸ₯‡35 Β· ⭐ 1.3K) - Extension for Scikit-learn is a seamless way to speed.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 86 Β· πŸ”€ 180 Β· πŸ“¦ 14K Β· πŸ“‹ 250 - 15% open Β· ⏱️ 28.10.2025):

    git clone https://github.com/intel/scikit-learn-intelex
    
  • PyPi (πŸ“₯ 89K / month Β· πŸ“¦ 74 Β· ⏱️ 22.10.2025):

    pip install scikit-learn-intelex
    
  • Conda (πŸ“₯ 650K Β· ⏱️ 30.10.2025):

    conda install -c conda-forge scikit-learn-intelex
    
</details> <details><summary><b><a href="https://github.com/scikit-learn-contrib/imbalanced-learn">imbalanced-learn</a></b> (πŸ₯‡33 Β· ⭐ 7.1K) - A Python Package to Tackle the Curse of Imbalanced.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 89 Β· πŸ”€ 1.3K Β· πŸ“‹ 630 - 8% open Β· ⏱️ 14.08.2025):

    git clone https://github.com/scikit-learn-contrib/imbalanced-learn
    
  • PyPi (πŸ“₯ 14M / month Β· πŸ“¦ 600 Β· ⏱️ 14.08.2025):

    pip install imbalanced-learn
    
  • Conda (πŸ“₯ 750K Β· ⏱️ 14.08.2025):

    conda install -c conda-forge imbalanced-learn
    
</details> <details><summary><b><a href="https://github.com/rasbt/mlxtend">MLxtend</a></b> (πŸ₯‡33 Β· ⭐ 5.1K) - A library of extension and helper modules for Pythons data.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 880 Β· πŸ“¦ 21K Β· πŸ“‹ 500 - 29% open Β· ⏱️ 19.06.2025):

    git clone https://github.com/rasbt/mlxtend
    
  • PyPi (πŸ“₯ 960K / month Β· πŸ“¦ 200 Β· ⏱️ 26.01.2025):

    pip install mlxtend
    
  • Conda (πŸ“₯ 460K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge mlxtend
    
</details> <details><summary><b><a href="https://github.com/scikit-learn-contrib/category_encoders">category_encoders</a></b> (πŸ₯ˆ31 Β· ⭐ 2.5K Β· πŸ’€) - A library of sklearn compatible categorical variable.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 71 Β· πŸ”€ 400 Β· πŸ“¦ 4.1K Β· πŸ“‹ 300 - 13% open Β· ⏱️ 24.03.2025):

    git clone https://github.com/scikit-learn-contrib/category_encoders
    
  • PyPi (πŸ“₯ 2.1M / month Β· πŸ“¦ 310 Β· ⏱️ 15.03.2025):

    pip install category_encoders
    
  • Conda (πŸ“₯ 370K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge category_encoders
    
</details> <details><summary><b><a href="https://github.com/koaning/scikit-lego">scikit-lego</a></b> (πŸ₯ˆ28 Β· ⭐ 1.4K) - Extra blocks for scikit-learn pipelines. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 69 Β· πŸ”€ 120 Β· πŸ“¦ 190 Β· πŸ“‹ 340 - 9% open Β· ⏱️ 21.10.2025):

    git clone https://github.com/koaning/scikit-lego
    
  • PyPi (πŸ“₯ 53K / month Β· πŸ“¦ 13 Β· ⏱️ 15.09.2025):

    pip install scikit-lego
    
  • Conda (πŸ“₯ 76K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge scikit-lego
    
</details> <details><summary><b><a href="https://github.com/guofei9987/scikit-opt">scikit-opt</a></b> (πŸ₯‰26 Β· ⭐ 6.2K) - Genetic Algorithm, Particle Swarm Optimization, Simulated.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 24 Β· πŸ”€ 1.1K Β· πŸ“¦ 280 Β· πŸ“‹ 180 - 37% open Β· ⏱️ 31.08.2025):

    git clone https://github.com/guofei9987/scikit-opt
    
  • PyPi (πŸ“₯ 9.1K / month Β· πŸ“¦ 15 Β· ⏱️ 14.01.2022):

    pip install scikit-opt
    
</details> <details><summary><b><a href="https://github.com/trent-b/iterative-stratification">iterative-stratification</a></b> (πŸ₯‰21 Β· ⭐ 880 Β· πŸ’€) - scikit-learn cross validators for iterative.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 75 Β· πŸ“¦ 620 Β· πŸ“‹ 27 - 7% open Β· ⏱️ 12.10.2024):

    git clone https://github.com/trent-b/iterative-stratification
    
  • PyPi (πŸ“₯ 54K / month Β· πŸ“¦ 15 Β· ⏱️ 12.10.2024):

    pip install iterative-stratification
    
</details> <details><summary><b><a href="https://github.com/scikit-tda/scikit-tda">scikit-tda</a></b> (πŸ₯‰19 Β· ⭐ 550) - Topological Data Analysis for Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 7 Β· πŸ”€ 54 Β· πŸ“¦ 93 Β· πŸ“‹ 23 - 17% open Β· ⏱️ 28.10.2025):

    git clone https://github.com/scikit-tda/scikit-tda
    
  • PyPi (πŸ“₯ 1.8K / month Β· ⏱️ 19.07.2024):

    pip install scikit-tda
    
</details> <details><summary>Show 11 hidden projects...</summary>
  • <b><a href="https://github.com/sebp/scikit-survival">scikit-survival</a></b> (πŸ₯ˆ32 Β· ⭐ 1.2K) - Survival analysis built on top of scikit-learn. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/iskandr/fancyimpute">fancyimpute</a></b> (πŸ₯ˆ27 Β· ⭐ 1.3K Β· πŸ’€) - Multivariate imputation and matrix completion.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/scikit-multilearn/scikit-multilearn">scikit-multilearn</a></b> (πŸ₯ˆ27 Β· ⭐ 950 Β· πŸ’€) - A scikit-learn based module for multi-label et. al... <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/TeamHG-Memex/sklearn-crfsuite">sklearn-crfsuite</a></b> (πŸ₯‰25 Β· ⭐ 430 Β· πŸ’€) - scikit-learn inspired API for CRFsuite. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/scikit-learn-contrib/skope-rules">skope-rules</a></b> (πŸ₯‰22 Β· ⭐ 650 Β· πŸ’€) - machine learning with logical rules in Python. <code><a href="https://tldrlegal.com/search?q=BSD-1-Clause">❗️BSD-1-Clause</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/yzhao062/combo">combo</a></b> (πŸ₯‰21 Β· ⭐ 660 Β· πŸ’€) - (AAAI 20) A Python Toolbox for Machine Learning Model.. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code> <code>xgboost</code>
  • <b><a href="https://github.com/mathurinm/celer">celer</a></b> (πŸ₯‰21 Β· ⭐ 230) - Fast solver for L1-type problems: Lasso, sparse Logisitic regression,.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/scikit-learn-contrib/lightning">sklearn-contrib-lightning</a></b> (πŸ₯‰20 Β· ⭐ 1.8K Β· πŸ’€) - Large-scale linear classification, regression and.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/amueller/dabl">dabl</a></b> (πŸ₯‰18 Β· ⭐ 730 Β· πŸ’€) - Data Analysis Baseline Library. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/scikit-learn-contrib/DESlib">DESlib</a></b> (πŸ₯‰18 Β· ⭐ 490 Β· πŸ’€) - A Python library for dynamic classifier and ensemble selection. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/skggm/skggm">skggm</a></b> (πŸ₯‰17 Β· ⭐ 250) - Scikit-learn compatible estimation of general graphical models. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
</details> <br>

Pytorch Utilities

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries that extend Pytorch with additional capabilities.

<details><summary><b><a href="https://github.com/huggingface/accelerate">accelerate</a></b> (πŸ₯‡43 Β· ⭐ 9.2K) - A simple way to launch, train, and use PyTorch models on.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 370 Β· πŸ”€ 1.2K Β· πŸ“¦ 110K Β· πŸ“‹ 1.9K - 5% open Β· ⏱️ 22.10.2025):

    git clone https://github.com/huggingface/accelerate
    
  • PyPi (πŸ“₯ 17M / month Β· πŸ“¦ 2.8K Β· ⏱️ 20.10.2025):

    pip install accelerate
    
  • Conda (πŸ“₯ 670K Β· ⏱️ 24.10.2025):

    conda install -c conda-forge accelerate
    
</details> <details><summary><b><a href="https://github.com/tinygrad/tinygrad">tinygrad</a></b> (πŸ₯‡33 Β· ⭐ 30K) - You like pytorch? You like micrograd? You love tinygrad!. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 420 Β· πŸ”€ 3.6K Β· πŸ“¦ 20 Β· πŸ“‹ 1K - 12% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/geohot/tinygrad
    
</details> <details><summary><b><a href="https://github.com/KevinMusgrave/pytorch-metric-learning">PML</a></b> (πŸ₯‡33 Β· ⭐ 6.2K) - The easiest way to use deep metric learning in your application. Modular,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 45 Β· πŸ”€ 660 Β· πŸ“¦ 2.9K Β· πŸ“‹ 530 - 14% open Β· ⏱️ 17.08.2025):

    git clone https://github.com/KevinMusgrave/pytorch-metric-learning
    
  • PyPi (πŸ“₯ 2.3M / month Β· πŸ“¦ 68 Β· ⏱️ 17.08.2025):

    pip install pytorch-metric-learning
    
  • Conda (πŸ“₯ 13K Β· ⏱️ 25.03.2025):

    conda install -c metric-learning pytorch-metric-learning
    
</details> <details><summary><b><a href="https://github.com/rtqichen/torchdiffeq">torchdiffeq</a></b> (πŸ₯‡31 Β· ⭐ 6.2K) - Differentiable ODE solvers with full GPU support and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 23 Β· πŸ”€ 940 Β· πŸ“¦ 5.5K Β· πŸ“‹ 230 - 35% open Β· ⏱️ 04.04.2025):

    git clone https://github.com/rtqichen/torchdiffeq
    
  • PyPi (πŸ“₯ 1M / month Β· πŸ“¦ 120 Β· ⏱️ 21.11.2024):

    pip install torchdiffeq
    
  • Conda (πŸ“₯ 24K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge torchdiffeq
    
</details> <details><summary><b><a href="https://github.com/google-research/torchsde">torchsde</a></b> (πŸ₯ˆ30 Β· ⭐ 1.7K Β· πŸ’€) - Differentiable SDE solvers with GPU support and efficient.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 210 Β· πŸ“¦ 5.5K Β· πŸ“‹ 84 - 36% open Β· ⏱️ 30.12.2024):

    git clone https://github.com/google-research/torchsde
    
  • PyPi (πŸ“₯ 4.6M / month Β· πŸ“¦ 37 Β· ⏱️ 26.09.2023):

    pip install torchsde
    
  • Conda (πŸ“₯ 46K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge torchsde
    
</details> <details><summary><b><a href="https://github.com/rusty1s/pytorch_scatter">torch-scatter</a></b> (πŸ₯ˆ26 Β· ⭐ 1.7K) - PyTorch Extension Library of Optimized Scatter Operations. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 34 Β· πŸ”€ 200 Β· πŸ“‹ 420 - 6% open Β· ⏱️ 12.08.2025):

    git clone https://github.com/rusty1s/pytorch_scatter
    
  • PyPi (πŸ“₯ 82K / month Β· πŸ“¦ 150 Β· ⏱️ 06.10.2023):

    pip install torch-scatter
    
  • Conda (πŸ“₯ 1M Β· ⏱️ 03.10.2025):

    conda install -c conda-forge pytorch_scatter
    
</details> <details><summary><b><a href="https://github.com/rusty1s/pytorch_sparse">PyTorch Sparse</a></b> (πŸ₯ˆ25 Β· ⭐ 1.1K) - PyTorch Extension Library of Optimized Autograd Sparse.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 48 Β· πŸ”€ 160 Β· πŸ“‹ 300 - 10% open Β· ⏱️ 12.08.2025):

    git clone https://github.com/rusty1s/pytorch_sparse
    
  • PyPi (πŸ“₯ 63K / month Β· πŸ“¦ 120 Β· ⏱️ 06.10.2023):

    pip install torch-sparse
    
  • Conda (πŸ“₯ 940K Β· ⏱️ 03.10.2025):

    conda install -c conda-forge pytorch_sparse
    
</details> <details><summary><b><a href="https://github.com/BloodAxe/pytorch-toolbelt">Pytorch Toolbelt</a></b> (πŸ₯‰24 Β· ⭐ 1.6K) - PyTorch extensions for fast R&D prototyping and Kaggle.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 9 Β· πŸ”€ 120 Β· πŸ“₯ 180 Β· πŸ“‹ 33 - 12% open Β· ⏱️ 09.10.2025):

    git clone https://github.com/BloodAxe/pytorch-toolbelt
    
  • PyPi (πŸ“₯ 8.3K / month Β· πŸ“¦ 12 Β· ⏱️ 21.11.2024):

    pip install pytorch_toolbelt
    
</details> <details><summary><b><a href="https://github.com/facebookresearch/madgrad">madgrad</a></b> (πŸ₯‰18 Β· ⭐ 800 Β· πŸ’€) - MADGRAD Optimization Method. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 3 Β· πŸ”€ 58 Β· πŸ“¦ 110 Β· ⏱️ 27.01.2025):

    git clone https://github.com/facebookresearch/madgrad
    
  • PyPi (πŸ“₯ 9.7K / month Β· πŸ“¦ 1 Β· ⏱️ 08.03.2022):

    pip install madgrad
    
</details> <details><summary><b><a href="https://github.com/szagoruyko/pytorchviz">pytorchviz</a></b> (πŸ₯‰14 Β· ⭐ 3.4K Β· πŸ’€) - A small package to create visualizations of PyTorch execution.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 6 Β· πŸ”€ 280 Β· πŸ“‹ 72 - 47% open Β· ⏱️ 30.12.2024):

    git clone https://github.com/szagoruyko/pytorchviz
    
</details> <details><summary>Show 22 hidden projects...</summary>
  • <b><a href="https://github.com/Cadene/pretrained-models.pytorch">pretrainedmodels</a></b> (πŸ₯ˆ29 Β· ⭐ 9.1K Β· πŸ’€) - Pretrained ConvNets for pytorch: NASNet, ResNeXt,.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/lukemelas/EfficientNet-PyTorch">EfficientNet-PyTorch</a></b> (πŸ₯ˆ28 Β· ⭐ 8.2K Β· πŸ’€) - A PyTorch implementation of EfficientNet. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/Lightning-Universe/lightning-flash">lightning-flash</a></b> (πŸ₯ˆ27 Β· ⭐ 1.7K Β· πŸ’€) - Your PyTorch AI Factory - Flash enables you to easily.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/jettify/pytorch-optimizer">pytorch-optimizer</a></b> (πŸ₯ˆ26 Β· ⭐ 3.1K Β· πŸ’€) - torch-optimizer -- collection of optimizers for.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/dreamquark-ai/tabnet">TabNet</a></b> (πŸ₯ˆ26 Β· ⭐ 2.9K Β· πŸ’€) - PyTorch implementation of TabNet paper :.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/rwightman/gen-efficientnet-pytorch">EfficientNets</a></b> (πŸ₯ˆ25 Β· ⭐ 1.6K Β· πŸ’€) - Pretrained EfficientNet, EfficientNet-Lite, MixNet,.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/sksq96/pytorch-summary">pytorch-summary</a></b> (πŸ₯‰24 Β· ⭐ 4.1K Β· πŸ’€) - Model summary in PyTorch similar to model.summary().. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/facebookresearch/higher">Higher</a></b> (πŸ₯‰23 Β· ⭐ 1.6K Β· πŸ’€) - higher is a pytorch library allowing users to obtain higher.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/karpathy/micrograd">micrograd</a></b> (πŸ₯‰22 Β· ⭐ 14K Β· πŸ’€) - A tiny scalar-valued autograd engine and a neural net library.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/asappresearch/sru">SRU</a></b> (πŸ₯‰22 Β· ⭐ 2.1K Β· πŸ’€) - Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755). <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/adobe/antialiased-cnns">Antialiased CNNs</a></b> (πŸ₯‰22 Β· ⭐ 1.7K Β· πŸ’€) - pip install antialiased-cnns to improve stability and.. <code><a href="https://tldrlegal.com/search?q=CC%20BY-NC-SA%204.0">❗️CC BY-NC-SA 4.0</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/Luolc/AdaBound">AdaBound</a></b> (πŸ₯‰21 Β· ⭐ 2.9K Β· πŸ’€) - An optimizer that trains as fast as Adam and as good as SGD. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/lucidrains/reformer-pytorch">reformer-pytorch</a></b> (πŸ₯‰21 Β· ⭐ 2.2K Β· πŸ’€) - Reformer, the efficient Transformer, in Pytorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/tristandeleu/pytorch-meta">Torchmeta</a></b> (πŸ₯‰21 Β· ⭐ 2K Β· πŸ’€) - A collection of extensions and data-loaders for few-shot.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/GRAAL-Research/poutyne">Poutyne</a></b> (πŸ₯‰21 Β· ⭐ 580) - A simplified framework and utilities for PyTorch. <code><a href="http://bit.ly/37RvQcA">❗️LGPL-3.0</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/lucidrains/performer-pytorch">Performer Pytorch</a></b> (πŸ₯‰19 Β· ⭐ 1.2K Β· πŸ’€) - An implementation of Performer, a linear attention-.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/harvardnlp/pytorch-struct">Torch-Struct</a></b> (πŸ₯‰19 Β· ⭐ 1.1K Β· πŸ’€) - Fast, general, and tested differentiable structured.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/lucidrains/lambda-networks">Lambda Networks</a></b> (πŸ₯‰17 Β· ⭐ 1.5K Β· πŸ’€) - Implementation of LambdaNetworks, a new approach to.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/achaiah/pywick">Pywick</a></b> (πŸ₯‰17 Β· ⭐ 400 Β· πŸ’€) - High-level batteries-included neural network training library for.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/TorchDrift/TorchDrift">TorchDrift</a></b> (πŸ₯‰15 Β· ⭐ 320 Β· πŸ’€) - Drift Detection for your PyTorch Models. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/abhishekkrthakur/tez">Tez</a></b> (πŸ₯‰14 Β· ⭐ 1.2K Β· πŸ’€) - Tez is a super-simple and lightweight Trainer for PyTorch. It.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/parrt/tensor-sensor">Tensor Sensor</a></b> (πŸ₯‰14 Β· ⭐ 810 Β· πŸ’€) - The goal of this library is to generate more helpful.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
</details> <br>

Database Clients

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

Libraries for connecting to, operating, and querying databases.

πŸ”—Β <b><a href="https://github.com/ml-tooling/best-of-python#database-clients">best-of-python - DB Clients</a></b> ( ⭐ 4.2K) - Collection of database clients for python.

<br>

Others

<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>

<details><summary><b><a href="https://github.com/scipy/scipy">scipy</a></b> (πŸ₯‡51 Β· ⭐ 14K) - Ecosystem of open-source software for mathematics, science, and engineering. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 1.8K Β· πŸ”€ 5.5K Β· πŸ“₯ 97K Β· πŸ“¦ 1.4M Β· πŸ“‹ 11K - 15% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/scipy/scipy
    
  • PyPi (πŸ“₯ 220M / month Β· πŸ“¦ 61K Β· ⏱️ 28.10.2025):

    pip install scipy
    
  • Conda (πŸ“₯ 70M Β· ⏱️ 29.10.2025):

    conda install -c conda-forge scipy
    
</details> <details><summary><b><a href="https://github.com/sympy/sympy">SymPy</a></b> (πŸ₯‡49 Β· ⭐ 14K) - A computer algebra system written in pure Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 1.4K Β· πŸ”€ 4.8K Β· πŸ“₯ 570K Β· πŸ“¦ 290K Β· πŸ“‹ 15K - 37% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/sympy/sympy
    
  • PyPi (πŸ“₯ 73M / month Β· πŸ“¦ 4.6K Β· ⏱️ 27.04.2025):

    pip install sympy
    
  • Conda (πŸ“₯ 11M Β· ⏱️ 29.04.2025):

    conda install -c conda-forge sympy
    
</details> <details><summary><b><a href="https://github.com/streamlit/streamlit">Streamlit</a></b> (πŸ₯‡47 Β· ⭐ 42K) - Streamlit A faster way to build and share data apps. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 570 Β· πŸ”€ 3.8K Β· πŸ“¦ 1M Β· πŸ“‹ 5.7K - 23% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/streamlit/streamlit
    
  • PyPi (πŸ“₯ 19M / month Β· πŸ“¦ 4.6K Β· ⏱️ 29.10.2025):

    pip install streamlit
    
</details> <details><summary><b><a href="https://github.com/gradio-app/gradio">Gradio</a></b> (πŸ₯‡46 Β· ⭐ 40K) - Wrap UIs around any model, share with anyone. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 700 Β· πŸ”€ 3.1K Β· πŸ“¦ 84K Β· πŸ“‹ 6.1K - 6% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/gradio-app/gradio
    
  • PyPi (πŸ“₯ 11M / month Β· πŸ“¦ 1.6K Β· ⏱️ 22.10.2025):

    pip install gradio
    
</details> <details><summary><b><a href="https://github.com/carla-simulator/carla">carla</a></b> (πŸ₯‡37 Β· ⭐ 13K) - Open-source simulator for autonomous driving research. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 190 Β· πŸ”€ 4.2K Β· πŸ“¦ 1.1K Β· πŸ“‹ 6.2K - 18% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/carla-simulator/carla
    
  • PyPi (πŸ“₯ 18K / month Β· πŸ“¦ 16 Β· ⏱️ 14.09.2025):

    pip install carla
    
</details> <details><summary><b><a href="https://github.com/HIPS/autograd">Autograd</a></b> (πŸ₯‡37 Β· ⭐ 7.4K) - Efficiently computes derivatives of NumPy code. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 64 Β· πŸ”€ 910 Β· πŸ“¦ 14K Β· πŸ“‹ 440 - 42% open Β· ⏱️ 27.10.2025):

    git clone https://github.com/HIPS/autograd
    
  • PyPi (πŸ“₯ 3.4M / month Β· πŸ“¦ 310 Β· ⏱️ 05.05.2025):

    pip install autograd
    
  • Conda (πŸ“₯ 680K Β· ⏱️ 05.05.2025):

    conda install -c conda-forge autograd
    
</details> <details><summary><b><a href="https://github.com/PennyLaneAI/pennylane">PennyLane</a></b> (πŸ₯‡37 Β· ⭐ 2.9K) - PennyLane is a cross-platform Python library for quantum.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 210 Β· πŸ”€ 700 Β· πŸ“₯ 100 Β· πŸ“¦ 1.9K Β· πŸ“‹ 1.7K - 25% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/PennyLaneAI/PennyLane
    
  • PyPi (πŸ“₯ 200K / month Β· πŸ“¦ 89 Β· ⏱️ 15.10.2025):

    pip install pennylane
    
  • Conda (πŸ“₯ 340K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge pennylane
    
</details> <details><summary><b><a href="https://github.com/yzhao062/pyod">PyOD</a></b> (πŸ₯ˆ36 Β· ⭐ 9.6K) - A Python Library for Outlier and Anomaly Detection, Integrating Classical.. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 64 Β· πŸ”€ 1.4K Β· πŸ“¦ 5.5K Β· πŸ“‹ 390 - 59% open Β· ⏱️ 29.04.2025):

    git clone https://github.com/yzhao062/pyod
    
  • PyPi (πŸ“₯ 840K / month Β· πŸ“¦ 130 Β· ⏱️ 29.04.2025):

    pip install pyod
    
  • Conda (πŸ“₯ 170K Β· ⏱️ 30.04.2025):

    conda install -c conda-forge pyod
    
</details> <details><summary><b><a href="https://github.com/simonw/datasette">Datasette</a></b> (πŸ₯ˆ35 Β· ⭐ 10K) - An open source multi-tool for exploring and publishing data. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 770 Β· πŸ“₯ 75 Β· πŸ“¦ 1.6K Β· πŸ“‹ 1.9K - 32% open Β· ⏱️ 26.10.2025):

    git clone https://github.com/simonw/datasette
    
  • PyPi (πŸ“₯ 180K / month Β· πŸ“¦ 480 Β· ⏱️ 22.04.2025):

    pip install datasette
    
  • Conda (πŸ“₯ 73K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge datasette
    
</details> <details><summary><b><a href="https://github.com/deepchem/deepchem">DeepChem</a></b> (πŸ₯ˆ34 Β· ⭐ 6.3K Β· πŸ“‰) - Democratizing Deep-Learning for Drug Discovery, Quantum.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 260 Β· πŸ”€ 1.9K Β· πŸ“¦ 650 Β· πŸ“‹ 2.1K - 40% open Β· ⏱️ 27.10.2025):

    git clone https://github.com/deepchem/deepchem
    
  • PyPi (πŸ“₯ 54K / month Β· πŸ“¦ 24 Β· ⏱️ 27.10.2025):

    pip install deepchem
    
  • Conda (πŸ“₯ 120K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge deepchem
    
</details> <details><summary><b><a href="https://github.com/serge-sans-paille/pythran">Pythran</a></b> (πŸ₯ˆ34 Β· ⭐ 2.1K) - Ahead of Time compiler for numeric kernels. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 75 Β· πŸ”€ 200 Β· πŸ“¦ 3.6K Β· πŸ“‹ 930 - 15% open Β· ⏱️ 30.09.2025):

    git clone https://github.com/serge-sans-paille/pythran
    
  • PyPi (πŸ“₯ 500K / month Β· πŸ“¦ 28 Β· ⏱️ 23.05.2025):

    pip install pythran
    
  • Conda (πŸ“₯ 1.3M Β· ⏱️ 07.07.2025):

    conda install -c conda-forge pythran
    
</details> <details><summary><b><a href="https://github.com/wireservice/agate">agate</a></b> (πŸ₯ˆ34 Β· ⭐ 1.2K) - A Python data analysis library that is optimized for humans instead of.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 55 Β· πŸ”€ 150 Β· πŸ“¦ 5.3K Β· πŸ“‹ 650 - 0% open Β· ⏱️ 27.10.2025):

    git clone https://github.com/wireservice/agate
    
  • PyPi (πŸ“₯ 24M / month Β· πŸ“¦ 54 Β· ⏱️ 29.01.2025):

    pip install agate
    
  • Conda (πŸ“₯ 410K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge agate
    
</details> <details><summary><b><a href="https://github.com/online-ml/river">River</a></b> (πŸ₯ˆ32 Β· ⭐ 5.6K) - Online machine learning in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 130 Β· πŸ”€ 590 Β· πŸ“¦ 800 Β· πŸ“‹ 630 - 19% open Β· ⏱️ 05.10.2025):

    git clone https://github.com/online-ml/river
    
  • PyPi (πŸ“₯ 91K / month Β· πŸ“¦ 64 Β· ⏱️ 25.11.2024):

    pip install river
    
  • Conda (πŸ“₯ 130K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge river
    
</details> <details><summary><b><a href="https://github.com/scikit-learn-contrib/hdbscan">hdbscan</a></b> (πŸ₯ˆ32 Β· ⭐ 3K) - A high performance implementation of HDBSCAN clustering. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 97 Β· πŸ”€ 500 Β· πŸ“¦ 7.6K Β· πŸ“‹ 530 - 67% open Β· ⏱️ 11.10.2025):

    git clone https://github.com/scikit-learn-contrib/hdbscan
    
  • PyPi (πŸ“₯ 1.1M / month Β· πŸ“¦ 350 Β· ⏱️ 18.11.2024):

    pip install hdbscan
    
  • Conda (πŸ“₯ 2.8M Β· ⏱️ 09.09.2025):

    conda install -c conda-forge hdbscan
    
</details> <details><summary><b><a href="https://github.com/open-edge-platform/anomalib">anomalib</a></b> (πŸ₯ˆ31 Β· ⭐ 5.1K Β· πŸ“‰) - An anomaly detection library comprising state-of-the-art.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 98 Β· πŸ”€ 820 Β· πŸ“₯ 42K Β· πŸ“¦ 200 Β· πŸ“‹ 1.2K - 6% open Β· ⏱️ 27.10.2025):

    git clone https://github.com/openvinotoolkit/anomalib
    
  • PyPi (πŸ“₯ 200K / month Β· πŸ“¦ 7 Β· ⏱️ 09.10.2025):

    pip install anomalib
    
</details> <details><summary><b><a href="https://github.com/pyjanitor-devs/pyjanitor">pyjanitor</a></b> (πŸ₯ˆ31 Β· ⭐ 1.5K) - Clean APIs for data cleaning. Python implementation of R package.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 110 Β· πŸ”€ 170 Β· πŸ“¦ 980 Β· πŸ“‹ 590 - 18% open Β· ⏱️ 21.10.2025):

    git clone https://github.com/pyjanitor-devs/pyjanitor
    
  • PyPi (πŸ“₯ 280K / month Β· πŸ“¦ 42 Β· ⏱️ 07.03.2025):

    pip install pyjanitor
    
  • Conda (πŸ“₯ 300K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge pyjanitor
    
</details> <details><summary><b><a href="https://github.com/uber/causalml">causalml</a></b> (πŸ₯ˆ30 Β· ⭐ 5.6K) - Uplift modeling and causal inference with machine learning.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 71 Β· πŸ”€ 830 Β· πŸ“¦ 310 Β· πŸ“‹ 420 - 10% open Β· ⏱️ 26.09.2025):

    git clone https://github.com/uber/causalml
    
  • PyPi (πŸ“₯ 79K / month Β· πŸ“¦ 10 Β· ⏱️ 09.07.2025):

    pip install causalml
    
</details> <details><summary><b><a href="https://github.com/dstackai/dstack">dstack</a></b> (πŸ₯ˆ30 Β· ⭐ 1.9K) - dstack is an open-source control plane for running development,.. <code><a href="http://bit.ly/3postzC">MPL-2.0</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 63 Β· πŸ”€ 200 Β· πŸ“¦ 22 Β· πŸ“‹ 1.5K - 6% open Β· ⏱️ 30.10.2025):

    git clone https://github.com/dstackai/dstack
    
  • PyPi (πŸ“₯ 4.2K / month Β· ⏱️ 30.10.2025):

    pip install dstack
    
</details> <details><summary><b><a href="https://github.com/tensorly/tensorly">tensorly</a></b> (πŸ₯ˆ30 Β· ⭐ 1.6K) - TensorLy: Tensor Learning in Python. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 73 Β· πŸ”€ 290 Β· πŸ“¦ 1.1K Β· πŸ“‹ 280 - 22% open Β· ⏱️ 05.05.2025):

    git clone https://github.com/tensorly/tensorly
    
  • PyPi (πŸ“₯ 130K / month Β· πŸ“¦ 99 Β· ⏱️ 12.11.2024):

    pip install tensorly
    
  • Conda (πŸ“₯ 380K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge tensorly
    
</details> <details><summary><b><a href="https://github.com/dbt-labs/metricflow">metricflow</a></b> (πŸ₯ˆ29 Β· ⭐ 1.3K) - MetricFlow allows you to define, build, and maintain metrics in.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 52 Β· πŸ”€ 130 Β· πŸ“¦ 37 Β· πŸ“‹ 370 - 27% open Β· ⏱️ 29.10.2025):

    git clone https://github.com/transform-data/metricflow
    
  • PyPi (πŸ“₯ 94K / month Β· πŸ“¦ 4 Β· ⏱️ 14.10.2025):

    pip install metricflow
    
</details> <details><summary><b><a href="https://github.com/sepandhaghighi/pycm">pycm</a></b> (πŸ₯ˆ28 Β· ⭐ 1.5K) - Multi-class confusion matrix library in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 18 Β· πŸ”€ 120 Β· πŸ“¦ 420 Β· πŸ“‹ 210 - 7% open Β· ⏱️ 14.10.2025):

    git clone https://github.com/sepandhaghighi/pycm
    
  • PyPi (πŸ“₯ 190K / month Β· πŸ“¦ 28 Β· ⏱️ 15.10.2025):

    pip install pycm
    
</details> <details><summary><b><a href="https://github.com/MaxHalford/prince">Prince</a></b> (πŸ₯ˆ28 Β· ⭐ 1.4K) - Multivariate exploratory data analysis in Python PCA, CA, MCA, MFA,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 190 Β· πŸ“¦ 770 Β· ⏱️ 04.08.2025):

    git clone https://github.com/MaxHalford/prince
    
  • PyPi (πŸ“₯ 230K / month Β· πŸ“¦ 23 Β· ⏱️ 04.08.2025):

    pip install prince
    
  • Conda (πŸ“₯ 28K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge prince-factor-analysis
    
</details> <details><summary><b><a href="https://github.com/google/trax">Trax</a></b> (πŸ₯‰27 Β· ⭐ 8.3K) - Trax Deep Learning with Clear Code and Speed. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 82 Β· πŸ”€ 830 Β· πŸ“¦ 230 Β· πŸ“‹ 250 - 50% open Β· ⏱️ 26.09.2025):

    git clone https://github.com/google/trax
    
  • PyPi (πŸ“₯ 4.3K / month Β· πŸ“¦ 1 Β· ⏱️ 26.10.2021):

    pip install trax
    
</details> <details><summary><b><a href="https://github.com/adapter-hub/adapters">adapter-transformers</a></b> (πŸ₯‰27 Β· ⭐ 2.8K) - A Unified Library for Parameter-Efficient and Modular.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code>huggingface</code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 17 Β· πŸ”€ 360 Β· πŸ“¦ 260 Β· πŸ“‹ 410 - 10% open Β· ⏱️ 12.10.2025):

    git clone https://github.com/Adapter-Hub/adapter-transformers
    
  • PyPi (πŸ“₯ 4.9K / month Β· πŸ“¦ 12 Β· ⏱️ 07.07.2024):

    pip install adapter-transformers
    
</details> <details><summary><b><a href="https://github.com/facebookresearch/AugLy">AugLy</a></b> (πŸ₯‰26 Β· ⭐ 5.1K) - A data augmentations library for audio, image, text, and video. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 42 Β· πŸ”€ 310 Β· πŸ“¦ 180 Β· πŸ“‹ 80 - 30% open Β· ⏱️ 27.10.2025):

    git clone https://github.com/facebookresearch/AugLy
    
  • PyPi (πŸ“₯ 13K / month Β· πŸ“¦ 4 Β· ⏱️ 05.12.2023):

    pip install augly
    
</details> <details><summary><b><a href="https://github.com/ContinualAI/avalanche">avalanche</a></b> (πŸ₯‰26 Β· ⭐ 2K Β· πŸ’€) - Avalanche: an End-to-End Library for Continual Learning based on.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 87 Β· πŸ”€ 310 Β· πŸ“₯ 60 Β· πŸ“¦ 140 Β· πŸ“‹ 840 - 13% open Β· ⏱️ 11.03.2025):

    git clone https://github.com/ContinualAI/avalanche
    
  • PyPi (πŸ“₯ 3.2K / month Β· πŸ“¦ 3 Β· ⏱️ 29.10.2024):

    pip install avalanche-lib
    
</details> <details><summary><b><a href="https://github.com/trevorstephens/gplearn">gplearn</a></b> (πŸ₯‰26 Β· ⭐ 1.8K) - Genetic Programming in Python, with a scikit-learn inspired API. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 12 Β· πŸ”€ 300 Β· πŸ“¦ 730 Β· πŸ“‹ 220 - 11% open Β· ⏱️ 23.07.2025):

    git clone https://github.com/trevorstephens/gplearn
    
  • PyPi (πŸ“₯ 20K / month Β· πŸ“¦ 19 Β· ⏱️ 03.05.2022):

    pip install gplearn
    
  • Conda (πŸ“₯ 11K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge gplearn
    
</details> <details><summary><b><a href="https://github.com/tableau/TabPy">TabPy</a></b> (πŸ₯‰26 Β· ⭐ 1.6K Β· πŸ’€) - Execute Python code on the fly and display results in Tableau.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 51 Β· πŸ”€ 600 Β· πŸ“¦ 220 Β· πŸ“‹ 320 - 6% open Β· ⏱️ 25.11.2024):

    git clone https://github.com/tableau/TabPy
    
  • PyPi (πŸ“₯ 7.1K / month Β· πŸ“¦ 2 Β· ⏱️ 25.11.2024):

    pip install tabpy
    
  • Conda (πŸ“₯ 5.8K Β· ⏱️ 22.04.2025):

    conda install -c anaconda tabpy-client
    
</details> <details><summary><b><a href="https://github.com/minrk/findspark">findspark</a></b> (πŸ₯‰25 Β· ⭐ 520) - Find pyspark to make it importable. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 16 Β· πŸ”€ 72 Β· πŸ“¦ 5.6K Β· πŸ“‹ 23 - 47% open Β· ⏱️ 04.09.2025):

    git clone https://github.com/minrk/findspark
    
  • PyPi (πŸ“₯ 2.6M / month Β· πŸ“¦ 100 Β· ⏱️ 11.02.2022):

    pip install findspark
    
  • Conda (πŸ“₯ 1M Β· ⏱️ 22.04.2025):

    conda install -c conda-forge findspark
    
</details> <details><summary><b><a href="https://github.com/vecxoz/vecstack">vecstack</a></b> (πŸ₯‰23 Β· ⭐ 700) - Python package for stacking (machine learning technique). <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 1 Β· πŸ”€ 82 Β· πŸ“¦ 570 Β· ⏱️ 28.09.2025):

    git clone https://github.com/vecxoz/vecstack
    
  • PyPi (πŸ“₯ 1.8K / month Β· πŸ“¦ 5 Β· ⏱️ 28.09.2025):

    pip install vecstack
    
  • Conda (πŸ“₯ 3K Β· ⏱️ 22.04.2025):

    conda install -c conda-forge vecstack
    
</details> <details><summary><b><a href="https://github.com/Project-MONAI/MONAILabel">MONAILabel</a></b> (πŸ₯‰22 Β· ⭐ 760) - MONAI Label is an intelligent open source image labeling and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 69 Β· πŸ”€ 240 Β· πŸ“₯ 130K Β· πŸ“‹ 560 - 26% open Β· ⏱️ 14.08.2025):

    git clone https://github.com/Project-MONAI/MONAILabel
    
  • PyPi (πŸ“₯ 200 / month Β· ⏱️ 01.10.2023):

    pip install monailabel-weekly
    
</details> <details><summary><b><a href="https://github.com/jmschrei/apricot">apricot</a></b> (πŸ₯‰22 Β· ⭐ 520) - apricot implements submodular optimization for the purpose of selecting.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 4 Β· πŸ”€ 49 Β· πŸ“₯ 33 Β· πŸ“¦ 200 Β· πŸ“‹ 34 - 38% open Β· ⏱️ 09.06.2025):

    git clone https://github.com/jmschrei/apricot
    
  • PyPi (πŸ“₯ 13K / month Β· πŸ“¦ 16 Β· ⏱️ 18.02.2021):

    pip install apricot-select
    
</details> <details><summary><b><a href="https://github.com/pykale/pykale">pykale</a></b> (πŸ₯‰21 Β· ⭐ 470) - Knowledge-Aware machine LEarning (KALE): accessible machine learning.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 28 Β· πŸ”€ 70 Β· πŸ“¦ 6 Β· πŸ“‹ 140 - 8% open Β· ⏱️ 14.10.2025):

    git clone https://github.com/pykale/pykale
    
  • PyPi (πŸ“₯ 72 / month Β· ⏱️ 12.04.2022):

    pip install pykale
    
</details> <details><summary><b><a href="https://github.com/yzhao062/SUOD">SUOD</a></b> (πŸ₯‰21 Β· ⭐ 390 Β· πŸ’€) - (MLSys 21) An Acceleration System for Large-scare Unsupervised.. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 3 Β· πŸ”€ 49 Β· πŸ“¦ 560 Β· πŸ“‹ 15 - 80% open Β· ⏱️ 24.03.2025):

    git clone https://github.com/yzhao062/SUOD
    
  • PyPi (πŸ“₯ 13K / month Β· πŸ“¦ 9 Β· ⏱️ 24.03.2025):

    pip install suod
    
</details> <details><summary><b><a href="https://github.com/infer-actively/pymdp">pymdp</a></b> (πŸ₯‰16 Β· ⭐ 570) - A Python implementation of active inference for Markov Decision Processes. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
  • GitHub (πŸ‘¨β€πŸ’» 19 Β· πŸ”€ 110 Β· πŸ“‹ 130 - 39% open Β· ⏱️ 09.09.2025):

    git clone https://github.com/infer-actively/pymdp
    
  • PyPi (πŸ“₯ 1.1K / month Β· ⏱️ 08.12.2022):

    pip install inferactively-pymdp
    
</details> <details><summary>Show 31 hidden projects...</summary>
  • <b><a href="https://github.com/inducer/pyopencl">pyopencl</a></b> (πŸ₯ˆ31 Β· ⭐ 1.1K) - OpenCL integration for Python, plus shiny features. <code>❗Unlicensed</code>
  • <b><a href="https://github.com/google-deepmind/pysc2">pysc2</a></b> (πŸ₯ˆ30 Β· ⭐ 8.2K Β· πŸ’€) - StarCraft II Learning Environment. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
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  • <b><a href="https://github.com/ljvmiranda921/pyswarms">PySwarms</a></b> (πŸ₯ˆ28 Β· ⭐ 1.4K Β· πŸ’€) - A research toolkit for particle swarm optimization in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/nicodv/kmodes">kmodes</a></b> (πŸ₯ˆ28 Β· ⭐ 1.3K Β· πŸ’€) - Python implementations of the k-modes and k-prototypes clustering.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
  • <b><a href="https://github.com/annoviko/pyclustering">pyclustering</a></b> (πŸ₯ˆ28 Β· ⭐ 1.2K Β· πŸ’€) - pyclustering is a Python, C++ data mining library. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
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  • <b><a href="https://github.com/scikit-learn-contrib/metric-learn">metric-learn</a></b> (πŸ₯‰26 Β· ⭐ 1.4K Β· πŸ’€) - Metric learning algorithms in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
  • <b><a href="https://github.com/sinaptik-ai/pandas-ai">pandas-ai</a></b> (πŸ₯‰25 Β· ⭐ 22K) - Chat with your database or your datalake (SQL, CSV, parquet)... <code>❗Unlicensed</code>
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</details>

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