lukasmasuch / best-of-ml-python
π A ranked list of awesome machine learning Python libraries. Updated weekly.
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Repository Summary (README)
PreviewThis 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"> π§ββοΈ 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> π« Subscribe to our <a href="https://mltooling.substack.com/subscribe">newsletter</a> for updates and trending projects. </p>
Contents
- Machine Learning Frameworks 64 projects
- Data Visualization 55 projects
- Text Data & NLP 103 projects
- Image Data 64 projects
- Graph Data 36 projects
- Audio Data 29 projects
- Geospatial Data 22 projects
- Financial Data 25 projects
- Time Series Data 29 projects
- Medical Data 19 projects
- Tabular Data 6 projects
- Optical Character Recognition 12 projects
- Data Containers & Structures 1 projects
- Data Loading & Extraction 1 projects
- Web Scraping & Crawling 1 projects
- Data Pipelines & Streaming 2 projects
- Distributed Machine Learning 36 projects
- Hyperparameter Optimization & AutoML 52 projects
- Reinforcement Learning 23 projects
- Recommender Systems 17 projects
- Privacy Machine Learning 7 projects
- Workflow & Experiment Tracking 40 projects
- Model Serialization & Deployment 20 projects
- Model Interpretability 55 projects
- Vector Similarity Search (ANN) 13 projects
- Probabilistics & Statistics 24 projects
- Adversarial Robustness 9 projects
- GPU & Accelerator Utilities 20 projects
- Tensorflow Utilities 16 projects
- Jax Utilities 3 projects
- Sklearn Utilities 19 projects
- Pytorch Utilities 32 projects
- Database Clients 1 projects
- Others 66 projects
Explanation
- π₯π₯π₯Β Combined project-quality score
- βοΈΒ Star count from GitHub
- π£Β New project (less than 6 months old)
- π€Β Inactive project (6 months no activity)
- πΒ Dead project (12 months no activity)
- ππΒ Project is trending up or down
- βΒ Project was recently added
- βοΈΒ Warning (e.g. missing/risky license)
- π¨βπ»Β Contributors count from GitHub
- πΒ Fork count from GitHub
- πΒ Issue count from GitHub
- β±οΈΒ Last update timestamp on package manager
- π₯Β Download count from package manager
- π¦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
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> (π₯56 Β· 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 (π¨βπ» 5K Β· π 75K Β· π¦ 540K Β· π 42K - 4% open Β· β±οΈ 30.10.2025):
git clone https://github.com/tensorflow/tensorflow -
PyPi (π₯ 26M / month Β· π¦ 9.6K Β· β±οΈ 13.08.2025):
pip install tensorflow -
Conda (π₯ 6M Β· β±οΈ 27.10.2025):
conda install -c conda-forge tensorflow -
Docker Hub (π₯ 81M Β· β 2.8K Β· β±οΈ 30.10.2025):
docker pull tensorflow/tensorflow
-
GitHub (π¨βπ» 6K Β· π 26K Β· π₯ 110K Β· π¦ 830K Β· π 56K - 30% open Β· β±οΈ 30.10.2025):
git clone https://github.com/pytorch/pytorch -
PyPi (π₯ 70M / month Β· π¦ 30K Β· β±οΈ 15.10.2025):
pip install torch -
Conda (π₯ 29M Β· β±οΈ 25.03.2025):
conda install -c pytorch pytorch
-
GitHub (π¨βπ» 3.4K Β· π 26K Β· π₯ 1.1K Β· π¦ 1.3M Β· π 12K - 17% open Β· β±οΈ 30.10.2025):
git clone https://github.com/scikit-learn/scikit-learn -
PyPi (π₯ 140M / month Β· π¦ 35K Β· β±οΈ 09.09.2025):
pip install scikit-learn -
Conda (π₯ 40M Β· β±οΈ 09.09.2025):
conda install -c conda-forge scikit-learn
-
GitHub (π¨βπ» 1.4K Β· π 20K Β· π¦ 300K Β· π 13K - 2% open Β· β±οΈ 30.10.2025):
git clone https://github.com/keras-team/keras -
PyPi (π₯ 19M / month Β· π¦ 2K Β· β±οΈ 27.10.2025):
pip install keras -
Conda (π₯ 4.5M Β· β±οΈ 28.10.2025):
conda install -c conda-forge keras
-
GitHub (π¨βπ» 670 Β· π 8.8K Β· π₯ 20K Β· π¦ 170K Β· π 5.6K - 8% open Β· β±οΈ 30.10.2025):
git clone https://github.com/dmlc/xgboost -
PyPi (π₯ 31M / month Β· π¦ 2.9K Β· β±οΈ 21.10.2025):
pip install xgboost -
Conda (π₯ 6.6M Β· β±οΈ 16.09.2025):
conda install -c conda-forge xgboost
-
GitHub (π¨βπ» 1.5K Β· π 5.9K Β· π₯ 15K Β· π¦ 8.8K Β· π 20K - 8% open Β· β±οΈ 30.10.2025):
git clone https://github.com/PaddlePaddle/Paddle -
PyPi (π₯ 1.6M / month Β· π¦ 280 Β· β±οΈ 30.10.2025):
pip install paddlepaddle
-
GitHub (π¨βπ» 980 Β· π 3.2K Β· π¦ 47K Β· π 6.6K - 24% open Β· β±οΈ 30.10.2025):
git clone https://github.com/google/jax -
PyPi (π₯ 12M / month Β· π¦ 3.1K Β· β±οΈ 15.10.2025):
pip install jax -
Conda (π₯ 3.2M Β· β±οΈ 06.10.2025):
conda install -c conda-forge jaxlib
-
GitHub (π¨βπ» 1K Β· π 3.6K Β· π₯ 15K Β· π¦ 48K Β· π 7.4K - 11% open Β· β±οΈ 29.10.2025):
git clone https://github.com/Lightning-AI/lightning -
PyPi (π₯ 9.8M / month Β· π¦ 1.8K Β· β±οΈ 05.09.2025):
pip install pytorch-lightning -
Conda (π₯ 1.7M Β· β±οΈ 05.09.2025):
conda install -c conda-forge pytorch-lightning
-
GitHub (π¨βπ» 470 Β· π 3.3K Β· π₯ 36 Β· π¦ 180K Β· π 5.8K - 50% open Β· β±οΈ 22.10.2025):
git clone https://github.com/statsmodels/statsmodels -
PyPi (π₯ 24M / month Β· π¦ 5.6K Β· β±οΈ 07.07.2025):
pip install statsmodels -
Conda (π₯ 22M Β· β±οΈ 01.10.2025):
conda install -c conda-forge statsmodels
-
GitHub (π¨βπ» 3.3K Β· π 29K Β· β±οΈ 30.10.2025):
git clone https://github.com/apache/spark -
PyPi (π₯ 47M / month Β· π¦ 2.1K Β· β±οΈ 30.10.2025):
pip install pyspark -
Conda (π₯ 4.2M Β· β±οΈ 08.09.2025):
conda install -c conda-forge pyspark
-
GitHub (π¨βπ» 330 Β· π 3.9K Β· π₯ 310K Β· π¦ 56K Β· π 3.6K - 12% open Β· β±οΈ 28.10.2025):
git clone https://github.com/microsoft/LightGBM -
PyPi (π₯ 11M / month Β· π¦ 1.6K Β· β±οΈ 15.02.2025):
pip install lightgbm -
Conda (π₯ 4.1M Β· β±οΈ 20.10.2025):
conda install -c conda-forge lightgbm
-
GitHub (π¨βπ» 1.4K Β· π 1.2K Β· π₯ 460K Β· π¦ 19 Β· π 2.5K - 25% open Β· β±οΈ 30.10.2025):
git clone https://github.com/catboost/catboost -
PyPi (π₯ 5.1M / month Β· π¦ 650 Β· β±οΈ 13.04.2025):
pip install catboost -
Conda (π₯ 2.2M Β· β±οΈ 09.08.2025):
conda install -c conda-forge catboost
-
GitHub (π¨βπ» 680 Β· π 7.6K Β· π¦ 23K Β· π 1.9K - 14% open Β· β±οΈ 26.10.2025):
git clone https://github.com/fastai/fastai -
PyPi (π₯ 640K / month Β· π¦ 340 Β· β±οΈ 26.10.2025):
pip install fastai
-
GitHub (π¨βπ» 2.1K Β· π 14K Β· π¦ 21 Β· β±οΈ 30.10.2025):
git clone https://github.com/apache/flink -
PyPi (π₯ 450K / month Β· π¦ 38 Β· β±οΈ 28.10.2025):
pip install apache-flink
-
GitHub (π¨βπ» 280 Β· π 740 Β· π₯ 61 Β· π¦ 15K Β· π 1.3K - 33% open Β· β±οΈ 27.10.2025):
git clone https://github.com/google/flax -
PyPi (π₯ 2M / month Β· π¦ 740 Β· β±οΈ 25.09.2025):
pip install flax -
Conda (π₯ 130K Β· β±οΈ 27.10.2025):
conda install -c conda-forge flax
-
GitHub (π¨βπ» 1K Β· π 660 Β· π¦ 3.9K Β· π 1.4K - 10% open Β· β±οΈ 16.10.2025):
git clone https://github.com/pytorch/ignite -
PyPi (π₯ 170K / month Β· π¦ 120 Β· β±οΈ 30.10.2025):
pip install pytorch-ignite -
Conda (π₯ 250K Β· β±οΈ 16.10.2025):
conda install -c pytorch ignite
-
GitHub (π¨βπ» 34 Β· π 380 Β· π¦ 82K Β· π 200 - 17% open Β· β±οΈ 12.08.2025):
git clone https://github.com/arogozhnikov/einops -
PyPi (π₯ 15M / month Β· π¦ 2.6K Β· β±οΈ 09.02.2025):
pip install einops -
Conda (π₯ 470K Β· β±οΈ 22.04.2025):
conda install -c conda-forge einops
-
GitHub (π¨βπ» 1.5K Β· π 5.6K Β· π 17K - 5% open Β· β±οΈ 10.10.2025):
git clone https://github.com/unifyai/ivy -
PyPi (π₯ 33K / month Β· π¦ 16 Β· β±οΈ 16.06.2025):
pip install ivy
-
GitHub (π¨βπ» 180 Β· π 2.2K Β· β±οΈ 24.03.2025):
git clone https://github.com/jina-ai/jina -
PyPi (π₯ 120K / month Β· π¦ 29 Β· β±οΈ 24.03.2025):
pip install jina -
Conda (π₯ 110K Β· β±οΈ 22.04.2025):
conda install -c conda-forge jina-core -
Docker Hub (π₯ 1.8M Β· β 9 Β· β±οΈ 24.03.2025):
docker pull jinaai/jina
-
GitHub (π¨βπ» 340 Β· π 1.7K Β· π 1.7K - 1% open Β· β±οΈ 27.10.2025):
git clone https://github.com/mlpack/mlpack -
PyPi (π₯ 4.7K / month Β· π¦ 6 Β· β±οΈ 22.05.2025):
pip install mlpack -
Conda (π₯ 410K Β· β±οΈ 22.04.2025):
conda install -c conda-forge mlpack
-
GitHub (π¨βπ» 67 Β· π 280 Β· π₯ 2K Β· π¦ 70K Β· π 160 - 14% open Β· β±οΈ 07.03.2025):
git clone https://github.com/explosion/thinc -
PyPi (π₯ 17M / month Β· π¦ 160 Β· β±οΈ 04.04.2025):
pip install thinc -
Conda (π₯ 3.9M Β· β±οΈ 06.07.2025):
conda install -c conda-forge thinc
-
GitHub (π¨βπ» 160 Β· π 1.2K Β· π¦ 340 Β· π 1.1K - 4% open Β· β±οΈ 17.10.2024):
git clone https://github.com/ludwig-ai/ludwig -
PyPi (π₯ 3.8K / month Β· π¦ 6 Β· β±οΈ 30.07.2024):
pip install ludwig
-
GitHub (π¨βπ» 68 Β· π 400 Β· π¦ 1.7K Β· π 540 - 12% open Β· β±οΈ 23.10.2025):
git clone https://github.com/skorch-dev/skorch -
PyPi (π₯ 150K / month Β· π¦ 110 Β· β±οΈ 08.08.2025):
pip install skorch -
Conda (π₯ 810K Β· β±οΈ 08.08.2025):
conda install -c conda-forge skorch
-
GitHub (π¨βπ» 61 Β· π 1.3K Β· π¦ 1.5K Β· π 190 - 16% open Β· β±οΈ 04.08.2025):
git clone https://github.com/deepmind/sonnet -
PyPi (π₯ 35K / month Β· π¦ 19 Β· β±οΈ 02.01.2024):
pip install dm-sonnet -
Conda (π₯ 47K Β· β±οΈ 22.04.2025):
conda install -c conda-forge sonnet
-
GitHub (π¨βπ» 90 Β· π 260 Β· π¦ 2.6K Β· π 250 - 29% open Β· β±οΈ 29.09.2025):
git clone https://github.com/deepmind/dm-haiku -
PyPi (π₯ 260K / month Β· π¦ 200 Β· β±οΈ 18.09.2025):
pip install dm-haiku -
Conda (π₯ 44K Β· β±οΈ 19.09.2025):
conda install -c conda-forge dm-haiku
-
GitHub (π¨βπ» 5K Β· π 100 Β· π₯ 31 Β· π 400 - 3% open Β· β±οΈ 29.10.2025):
git clone https://github.com/ROCmSoftwarePlatform/tensorflow-upstream -
PyPi (π₯ 1.7K / month Β· π¦ 9 Β· β±οΈ 10.01.2024):
pip install tensorflow-rocm
-
GitHub (π¨βπ» 97 Β· π 260 Β· π¦ 150 Β· π 570 - 36% open Β· β±οΈ 06.10.2025):
git clone https://github.com/geomstats/geomstats -
PyPi (π₯ 15K / month Β· π¦ 12 Β· β±οΈ 09.09.2024):
pip install geomstats -
Conda (π₯ 8.2K Β· β±οΈ 22.04.2025):
conda install -c conda-forge geomstats
-
GitHub (π¨βπ» 38 Β· π 170 Β· π¦ 480 Β· π 110 - 2% open Β· β±οΈ 29.10.2025):
git clone https://github.com/pyRiemann/pyRiemann -
PyPi (π₯ 75K / month Β· π¦ 31 Β· β±οΈ 23.07.2025):
pip install pyriemann -
Conda (π₯ 16K Β· β±οΈ 23.07.2025):
conda install -c conda-forge pyriemann
-
GitHub (π¨βπ» 120 Β· π 1.5K Β· π₯ 26 Β· π¦ 21 Β· π 1.8K - 25% open Β· β±οΈ 03.12.2024):
git clone https://github.com/numenta/nupic -
PyPi (π₯ 510 / month Β· β±οΈ 01.09.2016):
pip install nupic
-
GitHub (π¨βπ» 120 Β· π 360 Β· π₯ 7.8K Β· π 450 - 22% open Β· β±οΈ 20.03.2025):
git clone https://github.com/determined-ai/determined -
PyPi (π₯ 33K / month Β· π¦ 4 Β· β±οΈ 19.03.2025):
pip install determined
-
GitHub (π¨βπ» 76 Β· π 340 Β· π₯ 1K Β· π 95 - 36% open Β· β±οΈ 29.08.2025):
git clone https://github.com/sony/nnabla -
PyPi (π₯ 1.6K / month Β· π¦ 44 Β· β±οΈ 29.05.2024):
pip install nnabla
-
GitHub (π¨βπ» 53 Β· π 120 Β· π₯ 24 Β· π¦ 23 Β· π 350 - 33% open Β· β±οΈ 29.10.2025):
git clone https://github.com/deepinv/deepinv -
PyPi (π₯ 2.4K / month Β· β±οΈ 08.10.2025):
pip install deepinv
-
GitHub (π¨βπ» 38 Β· π 260 Β· π₯ 2.7K Β· π 670 - 0% open Β· β±οΈ 18.10.2024):
git clone https://github.com/towhee-io/towhee -
PyPi (π₯ 1.3K / month Β· β±οΈ 04.12.2023):
pip install towhee
-
GitHub (π¨βπ» 56 Β· π 170 Β· π¦ 16 Β· π 64 - 60% open Β· β±οΈ 23.04.2025):
git clone https://github.com/nubank/fklearn -
PyPi (π₯ 750 / month Β· β±οΈ 26.02.2025):
pip install fklearn
-
GitHub (π¨βπ» 16 Β· π 41 Β· π₯ 79 Β· β±οΈ 29.10.2025):
git clone https://github.com/run-house/runhouse -
PyPi (π₯ 4.5K / month Β· π¦ 1 Β· β±οΈ 10.03.2025):
pip install runhouse
-
GitHub (π¨βπ» 41 Β· π 130 Β· π¦ 2 Β· π 91 - 40% open Β· β±οΈ 28.10.2025):
git clone https://github.com/neoml-lib/neoml -
PyPi (π₯ 190 / month Β· β±οΈ 26.12.2023):
pip install neoml
-
GitHub (π¨βπ» 7 Β· π 100 Β· π¦ 72 Β· β±οΈ 09.07.2025):
git clone https://github.com/serengil/chefboost -
PyPi (π₯ 770 / month Β· β±οΈ 30.10.2024):
pip install chefboost
-
GitHub (π¨βπ» 12 Β· π 88 Β· π¦ 4 Β· π 81 - 48% open Β· β±οΈ 19.03.2025):
git clone https://github.com/Xtra-Computing/thundergbm -
PyPi (π₯ 220 / month Β· β±οΈ 19.09.2022):
pip install thundergbm
- <b><a href="https://github.com/davisking/dlib">dlib</a></b> (π₯40 Β· β 14K) - A toolkit for making real world machine learning and data analysis.. <code><a href="https://tldrlegal.com/search?q=BSL-1.0">βοΈBSL-1.0</a></code>
- <b><a href="https://github.com/apache/mxnet">MXNet</a></b> (π₯38 Β· β 21K Β· π) - 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> (π₯37 Β· β 10K Β· π) - 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> (π₯33 Β· β 37K) - Federated query engine for AI - The only MCP Server youll ever need. <code><a href="https://tldrlegal.com/search?q=ICU">βοΈICU</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> (π₯33 Β· β 8.6K Β· π) - 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> (π₯33 Β· β 5.9K Β· π) - 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> (π₯32 Β· β 11K Β· π) - 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> (π₯32 Β· β 6.3K Β· π) - 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> (π₯31 Β· β 9.6K Β· π) - 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> (π₯31 Β· β 3.4K Β· π) - 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> (π₯29 Β· β 18K Β· π) - 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> (π₯28 Β· β 3.9K Β· π) - 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> (π₯26 Β· β 3.1K Β· π) - 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> (π₯26 Β· β 1.3K Β· π) - 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> (π₯25 Β· β 740 Β· π) - 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> (π₯24 Β· β 3.1K Β· π) - 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> (π₯24 Β· β 2.7K Β· π) - 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> (π₯22 Β· β 3.9K Β· π) - 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> (π₯22 Β· β 1.6K Β· π) - 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> (π₯22 Β· β 640 Β· π) - 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> (π₯21 Β· β 5K Β· π) - 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> (π₯21 Β· β 2.4K Β· π) - 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> (π₯20 Β· β 770 Β· π) - 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> (π₯19 Β· β 480 Β· π) - 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> (π₯16 Β· β 4K Β· π) - 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> (π₯14 Β· β 300 Β· π) - 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>
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> (π₯49 Β· β 22K) - matplotlib: plotting with Python. <code>βUnlicensed</code></summary>-
GitHub (π¨βπ» 1.9K Β· π 8.1K Β· π¦ 1.9M Β· π 11K - 14% open Β· β±οΈ 30.10.2025):
git clone https://github.com/matplotlib/matplotlib -
PyPi (π₯ 120M / month Β· π¦ 68K Β· β±οΈ 09.10.2025):
pip install matplotlib -
Conda (π₯ 33M Β· β±οΈ 15.10.2025):
conda install -c conda-forge matplotlib
-
GitHub (π¨βπ» 300 Β· π 2.7K Β· π₯ 550 Β· π¦ 460K Β· π 3.3K - 21% open Β· β±οΈ 28.10.2025):
git clone https://github.com/plotly/plotly.py -
PyPi (π₯ 37M / month Β· π¦ 9.7K Β· β±οΈ 02.10.2025):
pip install plotly -
Conda (π₯ 12M Β· β±οΈ 03.10.2025):
conda install -c conda-forge plotly -
npm (π₯ 2.8K / month Β· π¦ 9 Β· β±οΈ 12.01.2021):
npm install plotlywidget
-
GitHub (π¨βπ» 190 Β· π 2.2K Β· π₯ 120 Β· π¦ 89K Β· π 2.1K - 27% open Β· β±οΈ 21.10.2025):
git clone https://github.com/plotly/dash -
PyPi (π₯ 5.5M / month Β· π¦ 1.9K Β· β±οΈ 22.10.2025):
pip install dash -
Conda (π₯ 2.1M Β· β±οΈ 11.08.2025):
conda install -c conda-forge dash
-
GitHub (π¨βπ» 720 Β· π 4.2K Β· π¦ 100K Β· π 8.1K - 10% open Β· β±οΈ 28.10.2025):
git clone https://github.com/bokeh/bokeh -
PyPi (π₯ 5M / month Β· π¦ 2.2K Β· β±οΈ 13.10.2025):
pip install bokeh -
Conda (π₯ 18M Β· β±οΈ 30.08.2025):
conda install -c conda-forge bokeh
-
GitHub (π¨βπ» 220 Β· π 2K Β· π₯ 510 Β· π¦ 700K Β· π 2.6K - 6% open Β· β±οΈ 10.07.2025):
git clone https://github.com/mwaskom/seaborn -
PyPi (π₯ 31M / month Β· π¦ 11K Β· β±οΈ 25.01.2024):
pip install seaborn -
Conda (π₯ 15M Β· β±οΈ 22.04.2025):
conda install -c conda-forge seaborn
-
GitHub (π¨βπ» 180 Β· π 800 Β· π₯ 280 Β· π¦ 240K Β· π 2.1K - 6% open Β· β±οΈ 27.10.2025):
git clone https://github.com/altair-viz/altair -
PyPi (π₯ 37M / month Β· π¦ 920 Β· β±οΈ 23.11.2024):
pip install altair -
Conda (π₯ 3M Β· β±οΈ 22.04.2025):
conda install -c conda-forge altair
-
GitHub (π¨βπ» 160 Β· π 680 Β· π¦ 1K Β· π 1.8K - 35% open Β· β±οΈ 29.10.2025):
git clone https://github.com/voxel51/fiftyone -
PyPi (π₯ 170K / month Β· π¦ 36 Β· β±οΈ 20.10.2025):
pip install fiftyone
-
GitHub (π¨βπ» 24 Β· π 220 Β· π¦ 95K Β· π 190 - 6% open Β· β±οΈ 26.10.2025):
git clone https://github.com/xflr6/graphviz -
PyPi (π₯ 26M / month Β· π¦ 3.2K Β· β±οΈ 15.06.2025):
pip install graphviz -
Conda (π₯ 59K Β· β±οΈ 22.04.2025):
conda install -c anaconda python-graphviz
-
GitHub (π¨βπ» 190 Β· π 590 Β· π₯ 960 Β· π¦ 5.2K Β· π 2K - 35% open Β· β±οΈ 28.10.2025):
git clone https://github.com/pyvista/pyvista -
PyPi (π₯ 1M / month Β· π¦ 820 Β· β±οΈ 26.08.2025):
pip install pyvista -
Conda (π₯ 810K Β· β±οΈ 10.10.2025):
conda install -c conda-forge pyvista
-
GitHub (π¨βπ» 150 Β· π 410 Β· π¦ 17K Β· π 3.4K - 31% open Β· β±οΈ 29.10.2025):
git clone https://github.com/holoviz/holoviews -
PyPi (π₯ 820K / month Β· π¦ 490 Β· β±οΈ 29.10.2025):
pip install holoviews -
Conda (π₯ 2.4M Β· β±οΈ 25.06.2025):
conda install -c conda-forge holoviews -
npm (π₯ 380 / month Β· π¦ 7 Β· β±οΈ 20.06.2025):
npm install @pyviz/jupyterlab_pyviz
-
GitHub (π¨βπ» 45 Β· π 2.9K Β· π₯ 75 Β· π¦ 5.5K Β· π 1.9K - 0% open Β· β±οΈ 10.10.2025):
git clone https://github.com/pyecharts/pyecharts -
PyPi (π₯ 530K / month Β· π¦ 280 Β· β±οΈ 10.10.2025):
pip install pyecharts
-
GitHub (π¨βπ» 300 Β· π 1.1K Β· π¦ 13K Β· π 1.4K - 31% open Β· β±οΈ 02.10.2025):
git clone https://github.com/pyqtgraph/pyqtgraph -
PyPi (π₯ 560K / month Β· π¦ 1K Β· β±οΈ 29.04.2024):
pip install pyqtgraph -
Conda (π₯ 880K Β· β±οΈ 22.04.2025):
conda install -c conda-forge pyqtgraph
-
GitHub (π¨βπ» 140 Β· π 1.7K Β· π₯ 490 Β· π¦ 6.9K Β· π 850 - 30% open Β· β±οΈ 19.09.2025):
git clone https://github.com/ydataai/pandas-profiling -
PyPi (π₯ 330K / month Β· π¦ 180 Β· β±οΈ 03.02.2023):
pip install pandas-profiling -
Conda (π₯ 590K Β· β±οΈ 22.04.2025):
conda install -c conda-forge pandas-profiling
-
GitHub (π¨βπ» 110 Β· π 240 Β· π¦ 13K Β· π 750 - 10% open Β· β±οΈ 16.10.2025):
git clone https://github.com/has2k1/plotnine -
PyPi (π₯ 2.2M / month Β· π¦ 400 Β· β±οΈ 15.07.2025):
pip install plotnine -
Conda (π₯ 560K Β· β±οΈ 15.07.2025):
conda install -c conda-forge plotnine
-
GitHub (π¨βπ» 140 Β· π 390 Β· π¦ 8.1K Β· π 1.3K - 23% open Β· β±οΈ 30.10.2025):
git clone https://github.com/SciTools/cartopy -
PyPi (π₯ 810K / month Β· π¦ 970 Β· β±οΈ 01.08.2025):
pip install cartopy -
Conda (π₯ 5.6M Β· β±οΈ 27.10.2025):
conda install -c conda-forge cartopy
-
GitHub (π¨βπ» 210 Β· π 620 Β· π¦ 2.1K Β· π 1.5K - 25% open Β· β±οΈ 13.10.2025):
git clone https://github.com/vispy/vispy -
PyPi (π₯ 190K / month Β· π¦ 200 Β· β±οΈ 19.05.2025):
pip install vispy -
Conda (π₯ 980K Β· β±οΈ 30.08.2025):
conda install -c conda-forge vispy -
npm (π₯ 12 / month Β· π¦ 3 Β· β±οΈ 15.03.2020):
npm install vispy
-
GitHub (π¨βπ» 63 Β· π 380 Β· π¦ 6.3K Β· π 620 - 24% open Β· β±οΈ 09.10.2025):
git clone https://github.com/holoviz/datashader -
PyPi (π₯ 280K / month Β· π¦ 250 Β· β±οΈ 05.08.2025):
pip install datashader -
Conda (π₯ 1.6M Β· β±οΈ 05.08.2025):
conda install -c conda-forge datashader
-
GitHub (π¨βπ» 21 Β· π 54 Β· π₯ 3.4K Β· π¦ 190 Β· π 740 - 21% open Β· β±οΈ 30.10.2025):
git clone https://github.com/JetBrains/lets-plot -
PyPi (π₯ 120K / month Β· π¦ 16 Β· β±οΈ 12.09.2025):
pip install lets-plot
-
GitHub (π¨βπ» 75 Β· π 2.3K Β· π¦ 21 Β· π 560 - 24% open Β· β±οΈ 31.08.2025):
git clone https://github.com/amueller/word_cloud -
PyPi (π₯ 2M / month Β· π¦ 550 Β· β±οΈ 10.11.2024):
pip install wordcloud -
Conda (π₯ 790K Β· β±οΈ 03.09.2025):
conda install -c conda-forge wordcloud
-
GitHub (π¨βπ» 100 Β· π 1.2K Β· π₯ 12K Β· π¦ 190 Β· π 890 - 12% open Β· β±οΈ 29.10.2025):
git clone https://github.com/finos/perspective -
PyPi (π₯ 17K / month Β· π¦ 31 Β· β±οΈ 28.10.2025):
pip install perspective-python -
Conda (π₯ 2.4M Β· β±οΈ 28.10.2025):
conda install -c conda-forge perspective -
npm (π₯ 600 / month Β· π¦ 6 Β· β±οΈ 03.09.2025):
npm install @finos/perspective-jupyterlab
-
GitHub (π¨βπ» 140 Β· π 850 Β· π¦ 1 Β· π 860 - 59% open Β· β±οΈ 26.10.2025):
git clone https://github.com/lmcinnes/umap -
PyPi (π₯ 2.7M / month Β· π¦ 1.3K Β· β±οΈ 03.07.2025):
pip install umap-learn -
Conda (π₯ 3.2M Β· β±οΈ 03.07.2025):
conda install -c conda-forge umap-learn
-
GitHub (π¨βπ» 52 Β· π 110 Β· π¦ 7.3K Β· π 940 - 41% open Β· β±οΈ 24.10.2025):
git clone https://github.com/holoviz/hvplot -
PyPi (π₯ 310K / month Β· π¦ 270 Β· β±οΈ 29.08.2025):
pip install hvplot -
Conda (π₯ 860K Β· β±οΈ 04.09.2025):
conda install -c conda-forge hvplot
-
GitHub (π¨βπ» 54 Β· π 360 Β· π¦ 7.6K Β· π 370 - 59% open Β· β±οΈ 27.07.2025):
git clone https://github.com/mpld3/mpld3 -
PyPi (π₯ 440K / month Β· π¦ 160 Β· β±οΈ 27.07.2025):
pip install mpld3 -
Conda (π₯ 280K Β· β±οΈ 28.07.2025):
conda install -c conda-forge mpld3 -
npm (π₯ 900 / month Β· π¦ 11 Β· β±οΈ 27.07.2025):
npm install mpld3
-
GitHub (π¨βπ» 66 Β· π 480 Β· π¦ 62 Β· π 650 - 42% open Β· β±οΈ 25.08.2025):
git clone https://github.com/bqplot/bqplot -
PyPi (π₯ 230K / month Β· π¦ 110 Β· β±οΈ 21.05.2025):
pip install bqplot -
Conda (π₯ 1.9M Β· β±οΈ 02.09.2025):
conda install -c conda-forge bqplot -
npm (π₯ 3K / month Β· π¦ 21 Β· β±οΈ 03.09.2025):
npm install bqplot
-
GitHub (π¨βπ» 31 Β· π 430 Β· π¦ 1.5K Β· π 610 - 10% open Β· β±οΈ 30.07.2025):
git clone https://github.com/man-group/dtale -
PyPi (π₯ 31K / month Β· π¦ 53 Β· β±οΈ 30.07.2025):
pip install dtale -
Conda (π₯ 480K Β· β±οΈ 30.07.2025):
conda install -c conda-forge dtale
-
GitHub (π¨βπ» 14 Β· π 170 Β· π¦ 1.1K Β· π 150 - 2% open Β· β±οΈ 27.10.2025):
git clone https://github.com/pavlin-policar/openTSNE -
PyPi (π₯ 58K / month Β· π¦ 69 Β· β±οΈ 27.10.2025):
pip install opentsne -
Conda (π₯ 500K Β· β±οΈ 27.10.2025):
conda install -c conda-forge opentsne
-
GitHub (π¨βπ» 14 Β· π 74 Β· π¦ 2K Β· π 190 - 32% open Β· β±οΈ 03.09.2025):
git clone https://github.com/predict-idlab/plotly-resampler -
PyPi (π₯ 370K / month Β· π¦ 38 Β· β±οΈ 29.08.2025):
pip install plotly-resampler -
Conda (π₯ 140K Β· β±οΈ 09.10.2025):
conda install -c conda-forge plotly-resampler
-
GitHub (π¨βπ» 23 Β· π 160 Β· π₯ 73 Β· π¦ 510 Β· π 200 - 34% open Β· β±οΈ 10.07.2025):
git clone https://github.com/ContextLab/hypertools -
PyPi (π₯ 1.1K / month Β· π¦ 2 Β· β±οΈ 09.07.2025):
pip install hypertools
-
GitHub (π¨βπ» 30 Β· π 180 Β· π₯ 1K Β· π 190 - 20% open Β· β±οΈ 23.06.2025):
git clone https://github.com/tensorflow/data-validation -
PyPi (π₯ 150K / month Β· π¦ 32 Β· β±οΈ 09.06.2025):
pip install tensorflow-data-validation
-
GitHub (π¨βπ» 27 Β· π 340 Β· π¦ 83 Β· π 86 - 62% open Β· β±οΈ 16.10.2024):
git clone https://github.com/spotify/chartify -
PyPi (π₯ 1.2K / month Β· π¦ 9 Β· β±οΈ 16.10.2024):
pip install chartify -
Conda (π₯ 40K Β· β±οΈ 22.04.2025):
conda install -c conda-forge chartify
-
GitHub (π¨βπ» 19 Β· π 36 Β· π₯ 280 Β· π¦ 22 Β· π 57 - 28% open Β· β±οΈ 04.09.2025):
git clone https://github.com/ing-bank/popmon -
PyPi (π₯ 3.4K / month Β· π¦ 4 Β· β±οΈ 04.09.2025):
pip install popmon
-
GitHub (π¨βπ» 15 Β· π 65 Β· π¦ 4 Β· π 110 - 14% open Β· β±οΈ 01.01.2025):
git clone https://github.com/vega/ipyvega -
PyPi (π₯ 26K / month Β· π¦ 17 Β· β±οΈ 25.09.2024):
pip install vega -
Conda (π₯ 940K Β· β±οΈ 04.10.2025):
conda install -c conda-forge vega
-
GitHub (π¨βπ» 6 Β· π 26 Β· π₯ 6.6K Β· π 150 - 36% open Β· β±οΈ 29.09.2025):
git clone https://github.com/vegafusion/vegafusion -
PyPi (π₯ 770 / month Β· π¦ 2 Β· β±οΈ 09.05.2024):
pip install vegafusion-jupyter -
Conda (π₯ 520K Β· β±οΈ 27.10.2025):
conda install -c conda-forge vegafusion-python-embed -
npm (π₯ 1.9K / month Β· π¦ 3 Β· β±οΈ 09.05.2024):
npm install vegafusion-jupyter
- <b><a href="https://github.com/ResidentMario/missingno">missingno</a></b> (π₯30 Β· β 4.2K Β· π) - 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> (π₯28 Β· β 7.4K Β· π) - 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> (π₯28 Β· β 3.1K Β· π) - 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> (π₯27 Β· β 980 Β· π) - 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> (π₯26 Β· β 3.1K Β· π) - 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> (π₯26 Β· β 1.9K Β· π) - 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> (π₯26 Β· 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> (π₯24 Β· β 3.3K) - A GUI for Pandas DataFrames. <code><a href="https://tldrlegal.com/search?q=MIT-0">βοΈMIT-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> (π₯24 Β· β 2.8K Β· π) - 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> (π₯24 Β· β 770 Β· π) - 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> (π₯23 Β· β 1.9K Β· π) - 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> (π₯22 Β· β 890 Β· π) - 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> (π₯21 Β· β 710 Β· π) - 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> (π₯21 Β· β 600 Β· π) - 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> (π₯21 Β· β 600 Β· π) - 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> (π₯20 Β· β 860 Β· π) - 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> (π₯18 Β· β 410 Β· π) - 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> (π₯18 Β· β 340 Β· π) - 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> (π₯16 Β· β 340 Β· π) - 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> (π₯16 Β· β 230 Β· π) - 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> (π₯15 Β· β 300 Β· π) - 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> (π₯11 Β· β 33 Β· π) - nptsne is a numpy compatible python binary package that offers a.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
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> (π₯54 Β· 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 (π¨βπ» 3.6K Β· π 31K Β· π¦ 400K Β· π 19K - 11% open Β· β±οΈ 30.10.2025):
git clone https://github.com/huggingface/transformers -
PyPi (π₯ 93M / month Β· π¦ 11K Β· β±οΈ 14.10.2025):
pip install transformers -
Conda (π₯ 3.3M Β· β±οΈ 14.10.2025):
conda install -c conda-forge transformers
-
GitHub (π¨βπ» 480 Β· π 3K Β· π¦ 410K Β· π 1.9K - 14% open Β· β±οΈ 22.10.2025):
git clone https://github.com/nltk/nltk -
PyPi (π₯ 42M / month Β· π¦ 6.3K Β· β±οΈ 01.10.2025):
pip install nltk -
Conda (π₯ 3.4M Β· β±οΈ 01.10.2025):
conda install -c conda-forge nltk
-
GitHub (π¨βπ» 960 Β· π 4.5K Β· π₯ 800 Β· π¦ 17K Β· π 7.8K - 17% open Β· β±οΈ 30.10.2025):
git clone https://github.com/BerriAI/litellm -
PyPi (π₯ 34M / month Β· π¦ 1.9K Β· β±οΈ 29.10.2025):
pip install litellm
-
GitHub (π¨βπ» 780 Β· π 4.5K Β· π₯ 4.9K Β· π¦ 140K Β· π 5.8K - 3% open Β· β±οΈ 28.10.2025):
git clone https://github.com/explosion/spaCy -
PyPi (π₯ 17M / month Β· π¦ 3.2K Β· β±οΈ 23.05.2025):
pip install spacy -
Conda (π₯ 6.5M Β· β±οΈ 06.07.2025):
conda install -c conda-forge spacy
-
GitHub (π¨βπ» 240 Β· π 2.7K Β· π¦ 120K Β· π 2.5K - 51% open Β· β±οΈ 22.10.2025):
git clone https://github.com/UKPLab/sentence-transformers -
PyPi (π₯ 17M / month Β· π¦ 3.7K Β· β±οΈ 22.10.2025):
pip install sentence-transformers -
Conda (π₯ 1M Β· β±οΈ 22.10.2025):
conda install -c conda-forge sentence-transformers
-
GitHub (π¨βπ» 460 Β· π 4.4K Β· π₯ 6.4K Β· π¦ 78K Β· π 1.9K - 21% open Β· β±οΈ 16.10.2025):
git clone https://github.com/RaRe-Technologies/gensim -
PyPi (π₯ 5.2M / month Β· π¦ 1.6K Β· β±οΈ 18.10.2025):
pip install gensim -
Conda (π₯ 1.8M Β· β±οΈ 22.04.2025):
conda install -c conda-forge gensim
-
GitHub (π¨βπ» 100 Β· π 1.3K Β· π₯ 110K Β· π¦ 120K Β· π 800 - 3% open Β· β±οΈ 04.10.2025):
git clone https://github.com/google/sentencepiece -
PyPi (π₯ 31M / month Β· π¦ 2.4K Β· β±οΈ 12.08.2025):
pip install sentencepiece -
Conda (π₯ 1.7M Β· β±οΈ 22.09.2025):
conda install -c conda-forge sentencepiece
-
GitHub (π¨βπ» 130 Β· π 970 Β· π₯ 86 Β· π¦ 180K Β· π 1.1K - 9% open Β· β±οΈ 16.10.2025):
git clone https://github.com/huggingface/tokenizers -
PyPi (π₯ 81M / month Β· π¦ 1.7K Β· β±οΈ 19.09.2025):
pip install tokenizers -
Conda (π₯ 3.6M Β· β±οΈ 19.09.2025):
conda install -c conda-forge tokenizers
-
GitHub (π¨βπ» 460 Β· π 3.2K Β· π₯ 520K Β· π¦ 21 Β· π 2.8K - 4% open Β· β±οΈ 29.10.2025):
git clone https://github.com/NVIDIA/NeMo -
PyPi (π₯ 810K / month Β· π¦ 18 Β· β±οΈ 27.10.2025):
pip install nemo-toolkit
-
GitHub (π¨βπ» 310 Β· π 2.5K Β· π¦ 1.3K Β· π 4.1K - 2% open Β· β±οΈ 30.10.2025):
git clone https://github.com/deepset-ai/haystack -
PyPi (π₯ 7.4K / month Β· π¦ 5 Β· β±οΈ 15.12.2021):
pip install haystack
-
GitHub (π¨βπ» 81 Β· π 1.1K Β· π¦ 17 Β· π 540 - 29% open Β· β±οΈ 30.10.2025):
git clone https://github.com/comet-ml/opik -
PyPi (π₯ 850K / month Β· π¦ 34 Β· β±οΈ 29.10.2025):
pip install opik
-
GitHub (π¨βπ» 110 Β· π 4.5K Β· π¦ 6.5K Β· π 1.7K - 6% open Β· β±οΈ 25.10.2025):
git clone https://github.com/gunthercox/ChatterBot -
PyPi (π₯ 20K / month Β· π¦ 19 Β· β±οΈ 16.10.2025):
pip install chatterbot
-
GitHub (π¨βπ» 280 Β· π 2.1K Β· π¦ 4.1K Β· π 2.4K - 1% open Β· β±οΈ 12.06.2025):
git clone https://github.com/flairNLP/flair -
PyPi (π₯ 180K / month Β· π¦ 160 Β· β±οΈ 05.02.2025):
pip install flair -
Conda (π₯ 49K Β· β±οΈ 22.04.2025):
conda install -c conda-forge python-flair
-
GitHub (π¨βπ» 37 Β· π 1.2K Β· π₯ 140 Β· π¦ 60K Β· π 280 - 25% open Β· β±οΈ 18.10.2025):
git clone https://github.com/sloria/TextBlob -
PyPi (π₯ 1.5M / month Β· π¦ 400 Β· β±οΈ 13.01.2025):
pip install textblob -
Conda (π₯ 340K Β· β±οΈ 22.04.2025):
conda install -c conda-forge textblob
-
GitHub (π¨βπ» 430 Β· π 6.6K Β· π₯ 440 Β· π¦ 4.4K Β· π 4.4K - 30% open Β· β±οΈ 30.09.2025):
git clone https://github.com/facebookresearch/fairseq -
PyPi (π₯ 77K / month Β· π¦ 120 Β· β±οΈ 27.06.2022):
pip install fairseq -
Conda (π₯ 170K Β· β±οΈ 02.10.2025):
conda install -c conda-forge fairseq
-
GitHub (π¨βπ» 72 Β· π 920 Β· π¦ 4.1K Β· π 950 - 10% open Β· β±οΈ 05.10.2025):
git clone https://github.com/stanfordnlp/stanza -
PyPi (π₯ 770K / month Β· π¦ 240 Β· β±οΈ 05.10.2025):
pip install stanza -
Conda (π₯ 9K Β· β±οΈ 25.03.2025):
conda install -c stanfordnlp stanza
-
GitHub (π¨βπ» 140 Β· π 1.9K Β· π₯ 500K Β· π¦ 120 Β· π 1.6K - 22% open Β· β±οΈ 30.09.2025):
git clone https://github.com/qdrant/qdrant
-
GitHub (π¨βπ» 120 Β· π 730 Β· π¦ 620 Β· π 910 - 2% open Β· β±οΈ 22.10.2025):
git clone https://github.com/JohnSnowLabs/spark-nlp -
PyPi (π₯ 1M / month Β· π¦ 39 Β· β±οΈ 22.10.2025):
pip install spark-nlp
-
GitHub (π¨βπ» 600 Β· π 4.9K Β· π 6.8K - 2% open Β· β±οΈ 26.08.2025):
git clone https://github.com/RasaHQ/rasa -
PyPi (π₯ 110K / month Β· π¦ 60 Β· β±οΈ 14.01.2025):
pip install rasa
-
GitHub (π¨βπ» 190 Β· π 360 Β· π¦ 10K Β· π 370 - 53% open Β· β±οΈ 18.08.2025):
git clone https://github.com/tensorflow/text -
PyPi (π₯ 6.8M / month Β· π¦ 230 Β· β±οΈ 04.04.2025):
pip install tensorflow-text
-
GitHub (π¨βπ» 41 Β· π 190 Β· π¦ 11 Β· π 120 - 17% open Β· β±οΈ 28.10.2025):
git clone https://github.com/snowballstem/snowball -
PyPi (π₯ 24M / month Β· π¦ 550 Β· β±οΈ 09.05.2025):
pip install snowballstemmer -
Conda (π₯ 11M Β· β±οΈ 20.05.2025):
conda install -c conda-forge snowballstemmer
-
GitHub (π¨βπ» 160 Β· π 810 Β· π 850 - 38% open Β· β±οΈ 10.09.2025):
git clone https://github.com/pytorch/text -
PyPi (π₯ 730K / month Β· π¦ 280 Β· β±οΈ 24.04.2024):
pip install torchtext
-
GitHub (π¨βπ» 37 Β· π 160 Β· π¦ 15K Β· β±οΈ 11.10.2025):
git clone https://github.com/jamesturk/jellyfish -
PyPi (π₯ 8.6M / month Β· π¦ 320 Β· β±οΈ 11.10.2025):
pip install jellyfish -
Conda (π₯ 1.7M Β· β±οΈ 22.04.2025):
conda install -c conda-forge jellyfish
-
GitHub (π¨βπ» 78 Β· π 1.2K Β· π¦ 440 Β· π 640 - 4% open Β· β±οΈ 26.11.2024):
git clone https://github.com/deepmipt/DeepPavlov -
PyPi (π₯ 11K / month Β· π¦ 4 Β· β±οΈ 12.08.2024):
pip install deeppavlov
-
GitHub (π¨βπ» 22 Β· π 120 Β· π₯ 100 Β· π¦ 33K Β· π 150 - 7% open Β· β±οΈ 30.10.2024):
git clone https://github.com/rspeer/python-ftfy -
PyPi (π₯ 11M / month Β· π¦ 570 Β· β±οΈ 26.10.2024):
pip install ftfy -
Conda (π₯ 380K Β· β±οΈ 22.04.2025):
conda install -c conda-forge ftfy
-
GitHub (π¨βπ» 38 Β· π 240 Β· π¦ 1.3K Β· π 330 - 11% open Β· β±οΈ 01.10.2025):
git clone https://github.com/allenai/scispacy -
PyPi (π₯ 42K / month Β· π¦ 50 Β· β±οΈ 01.10.2025):
pip install scispacy
-
GitHub (π¨βπ» 120 Β· π 340 Β· π₯ 160 Β· π¦ 300 Β· π 580 - 0% open Β· β±οΈ 21.10.2025):
git clone https://github.com/cltk/cltk -
PyPi (π₯ 14K / month Β· π¦ 17 Β· β±οΈ 21.10.2025):
pip install cltk
-
GitHub (π¨βπ» 34 Β· π 2K Β· π¦ 2 Β· π 170 - 75% open Β· β±οΈ 06.01.2025):
git clone https://github.com/dwyl/english-words -
PyPi (π₯ 78K / month Β· π¦ 15 Β· β±οΈ 14.08.2025):
pip install english-words
-
GitHub (π¨βπ» 110 Β· π 460 Β· π¦ 3.1K Β· π 2.2K - 0% open Β· β±οΈ 05.08.2025):
git clone https://github.com/recognai/rubrix -
PyPi (π₯ 1.2K / month Β· β±οΈ 24.10.2022):
pip install rubrix -
Conda (π₯ 52K Β· β±οΈ 22.04.2025):
conda install -c conda-forge rubrix
-
GitHub (π¨βπ» 72 Β· π 560 Β· π¦ 370 Β· π 820 - 9% open Β· β±οΈ 29.07.2025):
git clone https://github.com/dedupeio/dedupe -
PyPi (π₯ 59K / month Β· π¦ 19 Β· β±οΈ 15.08.2024):
pip install dedupe -
Conda (π₯ 130K Β· β±οΈ 22.04.2025):
conda install -c conda-forge dedupe
-
GitHub (π¨βπ» 18 Β· π 260 Β· π₯ 1.1K Β· π¦ 8.8K Β· β±οΈ 18.04.2025):
git clone https://github.com/life4/textdistance -
PyPi (π₯ 1.3M / month Β· π¦ 99 Β· β±οΈ 16.07.2024):
pip install textdistance -
Conda (π₯ 970K Β· β±οΈ 22.04.2025):
conda install -c conda-forge textdistance
-
GitHub (π¨βπ» 23 Β· π 170 Β· π₯ 610 Β· π¦ 2.4K Β· β±οΈ 26.05.2025):
git clone https://github.com/explosion/spacy-transformers -
PyPi (π₯ 270K / month Β· π¦ 110 Β· β±οΈ 26.05.2025):
pip install spacy-transformers -
Conda (π₯ 140K Β· β±οΈ 22.04.2025):
conda install -c conda-forge spacy-transformers
-
GitHub (π¨βπ» 14 Β· π 130 Β· π₯ 1.9M Β· π¦ 980 Β· π 67 - 55% open Β· β±οΈ 29.07.2025):
git clone https://github.com/unitaryai/detoxify -
PyPi (π₯ 140K / month Β· π¦ 30 Β· β±οΈ 01.02.2024):
pip install detoxify
-
GitHub (π¨βπ» 14 Β· π 290 Β· π¦ 670 Β· π 100 - 22% open Β· β±οΈ 29.04.2025):
git clone https://github.com/JasonKessler/scattertext -
PyPi (π₯ 7.5K / month Β· π¦ 5 Β· β±οΈ 23.09.2024):
pip install scattertext -
Conda (π₯ 140K Β· β±οΈ 22.04.2025):
conda install -c conda-forge scattertext
-
GitHub (π¨βπ» 61 Β· π 780 Β· π 450 - 23% open Β· β±οΈ 28.04.2025):
git clone https://github.com/google-research/text-to-text-transfer-transformer -
PyPi (π₯ 83K / month Β· π¦ 2 Β· β±οΈ 18.10.2021):
pip install t5
-
GitHub (π¨βπ» 34 Β· π 730 Β· π¦ 25 Β· β±οΈ 19.07.2025):
git clone https://github.com/zjunlp/deepke -
PyPi (π₯ 950 / month Β· β±οΈ 21.09.2023):
pip install deepke
-
GitHub (π¨βπ» 20 Β· π 240 Β· π₯ 73K Β· π¦ 470 Β· π 120 - 20% open Β· β±οΈ 23.04.2025):
git clone https://github.com/explosion/sense2vec -
PyPi (π₯ 3.4K / month Β· π¦ 13 Β· β±οΈ 19.04.2021):
pip install sense2vec -
Conda (π₯ 67K Β· β±οΈ 22.04.2025):
conda install -c conda-forge sense2vec
-
GitHub (π¨βπ» 24 Β· π 79 Β· π¦ 16 Β· π 190 - 39% open Β· β±οΈ 21.10.2025):
git clone https://github.com/IndicoDataSolutions/finetune -
PyPi (π₯ 2.7K / month Β· π¦ 2 Β· β±οΈ 29.09.2023):
pip install finetune
-
GitHub (π¨βπ» 14 Β· π 69 Β· π¦ 330 Β· π 130 - 16% open Β· β±οΈ 22.03.2025):
git clone https://github.com/EricFillion/happy-transformer -
PyPi (π₯ 2.7K / month Β· π¦ 5 Β· β±οΈ 05.08.2023):
pip install happytransformer
-
GitHub (π¨βπ» 60 Β· π 320 Β· π₯ 21 Β· π 310 - 3% open Β· β±οΈ 24.10.2024):
git clone https://github.com/awslabs/sockeye -
PyPi (π₯ 580 / month Β· β±οΈ 03.03.2023):
pip install sockeye
-
GitHub (π¨βπ» 21 Β· π 76 Β· π₯ 710 Β· π¦ 36 Β· π 39 - 38% open Β· β±οΈ 03.09.2025):
git clone https://github.com/unum-cloud/uform -
PyPi (π₯ 490 / month Β· π¦ 2 Β· β±οΈ 03.09.2025):
pip install uform
-
GitHub (π¨βπ» 10 Β· π 76 Β· π¦ 34 Β· π 74 - 28% open Β· β±οΈ 28.10.2025):
git clone https://github.com/webis-de/small-text -
PyPi (π₯ 390 / month Β· β±οΈ 17.08.2025):
pip install small-text -
Conda (π₯ 19K Β· β±οΈ 17.08.2025):
conda install -c conda-forge small-text
-
GitHub (π¨βπ» 10 Β· π 60 Β· π₯ 140 Β· π¦ 180 Β· π 29 - 37% open Β· β±οΈ 09.09.2025):
git clone https://github.com/dsfsi/textaugment -
PyPi (π₯ 4.2K / month Β· π¦ 4 Β· β±οΈ 16.11.2023):
pip install textaugment
-
GitHub (π¨βπ» 4 Β· π 61 Β· π¦ 13 Β· π 16 - 43% open Β· β±οΈ 24.06.2025):
git clone https://github.com/facebookresearch/vizseq -
PyPi (π₯ 120 / month Β· β±οΈ 07.08.2020):
pip install vizseq
- <b><a href="https://github.com/allenai/allennlp">AllenNLP</a></b> (π₯36 Β· β 12K Β· π) - 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> (π₯34 Β· β 26K Β· π) - 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> (π₯33 Β· β 7K Β· π) - 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> (π₯32 Β· β 11K Β· π) - 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> (π₯31 Β· β 9.3K Β· π) - Fuzzy String Matching in Python. <code><a href="http://bit.ly/2KucAZR">βοΈGPL-2.0</a></code>
- <b><a href="https://github.com/miso-belica/sumy">Sumy</a></b> (π₯30 Β· β 3.6K Β· π) - 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> (π₯30 Β· β 1.6K) - Underthesea - Vietnamese NLP Toolkit. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/makcedward/nlpaug">nlpaug</a></b> (π₯29 Β· β 4.6K Β· π) - 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> (π₯28 Β· β 4.9K Β· π) - 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> (π₯28 Β· β 2.2K Β· π) - NLP, before and after spaCy. <code>βUnlicensed</code>
- <b><a href="https://github.com/DerwenAI/pytextrank">PyTextRank</a></b> (π₯28 Β· β 2.2K Β· π) - 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> (π₯27 Β· β 20K Β· π) - 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> (π₯27 Β· β 3.1K Β· π) - 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> (π₯27 Β· β 2.3K Β· π) - Multilingual text (NLP) processing toolkit. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/vi3k6i5/flashtext">flashtext</a></b> (π₯26 Β· β 5.7K Β· π) - 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> (π₯26 Β· β 2.4K Β· π) - 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> (π₯26 Β· β 880 Β· π) - 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> (π₯25 Β· β 2.9K Β· π) - 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> (π₯25 Β· β 2.6K Β· π) - 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> (π₯25 Β· β 2.2K Β· π) - 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> (π₯25 Β· β 640 Β· π) - Pure-Python full-text search library. <code><a href="https://tldrlegal.com/search?q=BSD-1-Clause">βοΈBSD-1-Clause</a></code>
- <b><a href="https://github.com/facebookresearch/pytext">PyText</a></b> (π₯24 Β· β 6.3K Β· π) - 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> (π₯24 Β· β 4.9K Β· π) - 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> (π₯24 Β· β 4.7K Β· π) - 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> (π₯24 Β· β 3.9K Β· π) - 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> (π₯24 Β· β 3.9K Β· π) - 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> (π₯24 Β· β 3K Β· π) - 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> (π₯24 Β· β 970 Β· π) - 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> (π₯23 Β· β 2.4K Β· π) - 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> (π₯23 Β· β 1.8K Β· π) - 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> (π₯22 Β· β 3.4K Β· π) - 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> (π₯22 Β· β 2.4K Β· π) - 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> (π₯22 Β· β 1.7K Β· π) - 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> (π₯22 Β· 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> (π₯21 Β· β 2.9K Β· π) - 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> (π₯21 Β· β 2.9K Β· π) - 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> (π₯21 Β· β 1.5K Β· π) - 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> (π₯20 Β· β 3.3K Β· π) - 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> (π₯20 Β· β 1.9K Β· π) - 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> (π₯20 Β· β 1.6K Β· π) - 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> (π₯20 Β· β 300 Β· π) - 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> (π₯19 Β· β 230 Β· π) - 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> (π₯19 Β· β 230 Β· π) - Yet another Python binding for fastText. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/anhaidgroup/deepmatcher">DeepMatcher</a></b> (π₯18 Β· β 5.2K Β· π) - 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> (π₯18 Β· β 670 Β· π) - 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> (π₯18 Β· β 590 Β· π) - 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> (π₯18 Β· β 340 Β· π) - 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> (π₯17 Β· β 1.7K Β· π) - 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> (π₯16 Β· β 4.4K Β· π) - 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> (π₯15 Β· β 1.2K Β· π) - Entity Linker solution. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/RUCAIBox/TextBox">TextBox</a></b> (π₯15 Β· β 1.1K Β· π) - 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> (π₯15 Β· β 830 Β· π) - 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> (π₯15 Β· β 240 Β· π) - 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> (π₯14 Β· β 260 Β· π) - 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> (π₯14 Β· β 230 Β· π) - 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> (π₯13 Β· β 290 Β· π) - 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> (π₯13 Β· β 230 Β· π) - 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> (π₯12 Β· β 200 Β· π) - 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> (π₯12 Β· β 110 Β· π) - A spaCy wrapper for DBpedia Spotlight. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code>spacy</code>
Image Data
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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> (π₯49 Β· β 13K) - Python Imaging Library (Fork). <code><a href="https://tldrlegal.com/search?q=PIL">βοΈPIL</a></code></summary>-
GitHub (π¨βπ» 490 Β· π 2.3K Β· π¦ 2.4M Β· π 3.4K - 3% open Β· β±οΈ 27.10.2025):
git clone https://github.com/python-pillow/Pillow -
PyPi (π₯ 220M / month Β· π¦ 20K Β· β±οΈ 15.10.2025):
pip install Pillow -
Conda (π₯ 62M Β· β±οΈ 28.10.2025):
conda install -c conda-forge pillow
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GitHub (π¨βπ» 180 Β· π 5.1K Β· π₯ 8.4M Β· π¦ 62K Β· π 1K - 4% open Β· β±οΈ 30.10.2025):
git clone https://github.com/rwightman/pytorch-image-models -
PyPi (π₯ 11M / month Β· π¦ 1.5K Β· β±οΈ 24.10.2025):
pip install timm -
Conda (π₯ 470K Β· β±οΈ 24.10.2025):
conda install -c conda-forge timm
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GitHub (π¨βπ» 660 Β· π 7.2K Β· π₯ 41K Β· π¦ 21 Β· π 3.8K - 30% open Β· β±οΈ 27.10.2025):
git clone https://github.com/pytorch/vision -
PyPi (π₯ 26M / month Β· π¦ 8.4K Β· β±οΈ 15.10.2025):
pip install torchvision -
Conda (π₯ 3.1M Β· β±οΈ 23.10.2025):
conda install -c conda-forge torchvision
-
GitHub (π¨βπ» 190 Β· π 1.9K Β· π¦ 67K Β· π 1.7K - 3% open Β· β±οΈ 25.09.2025):
git clone https://github.com/Zulko/moviepy -
PyPi (π₯ 4.3M / month Β· π¦ 1.2K Β· β±οΈ 21.05.2025):
pip install moviepy -
Conda (π₯ 360K Β· β±οΈ 22.04.2025):
conda install -c conda-forge moviepy
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GitHub (π¨βπ» 300 Β· π 1.1K Β· π₯ 2.2K Β· π¦ 17K Β· π 1K - 32% open Β· β±οΈ 30.10.2025):
git clone https://github.com/kornia/kornia -
PyPi (π₯ 3M / month Β· π¦ 340 Β· β±οΈ 08.05.2025):
pip install kornia -
Conda (π₯ 260K Β· β±οΈ 08.05.2025):
conda install -c conda-forge kornia
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GitHub (π¨βπ» 130 Β· π 330 Β· π₯ 1.9K Β· π¦ 180K Β· π 620 - 16% open Β· β±οΈ 24.10.2025):
git clone https://github.com/imageio/imageio -
PyPi (π₯ 36M / month Β· π¦ 2.6K Β· β±οΈ 20.01.2025):
pip install imageio -
Conda (π₯ 8.5M Β· β±οΈ 22.04.2025):
conda install -c conda-forge imageio
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GitHub (π¨βπ» 96 Β· π 2.8K Β· π¦ 8.4K Β· π 1.2K - 0% open Β· β±οΈ 21.10.2025):
git clone https://github.com/serengil/deepface -
PyPi (π₯ 280K / month Β· π¦ 78 Β· β±οΈ 05.08.2025):
pip install deepface
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GitHub (π¨βπ» 67 Β· π 5.7K Β· π₯ 11M Β· π¦ 4.8K Β· π 2.6K - 46% open Β· β±οΈ 27.09.2025):
git clone https://github.com/deepinsight/insightface -
PyPi (π₯ 350K / month Β· π¦ 30 Β· β±οΈ 17.12.2022):
pip install insightface
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GitHub (π¨βπ» 170 Β· π 1.7K Β· π 1.5K - 14% open Β· β±οΈ 25.06.2025):
git clone https://github.com/albumentations-team/albumentations -
PyPi (π₯ 4.6M / month Β· π¦ 730 Β· β±οΈ 27.05.2025):
pip install albumentations -
Conda (π₯ 340K Β· β±οΈ 28.05.2025):
conda install -c conda-forge albumentations
-
GitHub (π¨βπ» 56 Β· π 950 Β· π¦ 610K Β· π 890 - 19% open Β· β±οΈ 30.07.2025):
git clone https://github.com/opencv/opencv-python -
PyPi (π₯ 29M / month Β· π¦ 15K Β· β±οΈ 07.07.2025):
pip install opencv-python
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GitHub (π¨βπ» 280 Β· π 7.5K Β· π¦ 2.6K Β· π 3.6K - 14% open Β· β±οΈ 27.10.2025):
git clone https://github.com/facebookresearch/detectron2 -
PyPi (π¦ 13 Β· β±οΈ 06.02.2020):
pip install detectron2 -
Conda (π₯ 820K Β· β±οΈ 02.06.2025):
conda install -c conda-forge detectron2
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GitHub (π¨βπ» 110 Β· π 200 Β· π₯ 52K Β· π¦ 21K Β· π 440 - 5% open Β· β±οΈ 06.10.2025):
git clone https://github.com/emcconville/wand -
PyPi (π₯ 2.2M / month Β· π¦ 260 Β· β±οΈ 03.11.2023):
pip install wand -
Conda (π₯ 180K Β· β±οΈ 22.04.2025):
conda install -c conda-forge wand
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GitHub (π¨βπ» 29 Β· π 340 Β· π¦ 18K Β· π 150 - 15% open Β· β±οΈ 17.04.2025):
git clone https://github.com/JohannesBuchner/imagehash -
PyPi (π₯ 5.6M / month Β· π¦ 270 Β· β±οΈ 01.02.2025):
pip install ImageHash -
Conda (π₯ 500K Β· β±οΈ 22.04.2025):
conda install -c conda-forge imagehash
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GitHub (π¨βπ» 24 Β· π 3.4K Β· π¦ 21 Β· π 290 - 49% open Β· β±οΈ 28.10.2025):
git clone https://github.com/lucidrains/vit-pytorch -
PyPi (π₯ 31K / month Β· π¦ 28 Β· β±οΈ 27.10.2025):
pip install vit-pytorch
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GitHub (π¨βπ» 130 Β· π 1.7K Β· π¦ 1.5K Β· π 2.2K - 0% open Β· β±οΈ 10.10.2025):
git clone https://github.com/PaddlePaddle/PaddleSeg -
PyPi (π₯ 3.8K / month Β· π¦ 7 Β· β±οΈ 30.11.2022):
pip install paddleseg
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GitHub (π¨βπ» 69 Β· π 700 Β· π₯ 43K Β· π¦ 1.9K Β· β±οΈ 28.10.2025):
git clone https://github.com/obss/sahi -
PyPi (π₯ 140K / month Β· π¦ 43 Β· β±οΈ 28.09.2025):
pip install sahi -
Conda (π₯ 120K Β· β±οΈ 29.09.2025):
conda install -c conda-forge sahi
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GitHub (π¨βπ» 72 Β· π 310 Β· π¦ 510 Β· π 610 - 12% open Β· β±οΈ 25.09.2025):
git clone https://github.com/lightly-ai/lightly -
PyPi (π₯ 190K / month Β· π¦ 20 Β· β±οΈ 22.07.2025):
pip install lightly
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GitHub (π¨βπ» 68 Β· π 580 Β· π₯ 6.5M Β· π 440 - 6% open Β· β±οΈ 07.09.2025):
git clone https://github.com/mindee/doctr -
PyPi (π₯ 2M / month Β· π¦ 18 Β· β±οΈ 09.07.2025):
pip install python-doctr
-
GitHub (π¨βπ» 190 Β· π 3K Β· π 5.7K - 17% open Β· β±οΈ 10.10.2025):
git clone https://github.com/PaddlePaddle/PaddleDetection -
PyPi (π₯ 2.2K / month Β· π¦ 2 Β· β±οΈ 19.09.2022):
pip install paddledet
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GitHub (π¨βπ» 15 Β· π 530 Β· π₯ 76 Β· π¦ 9.2K Β· π 130 - 37% open Β· β±οΈ 08.10.2024):
git clone https://github.com/ipazc/mtcnn -
PyPi (π₯ 210K / month Β· π¦ 73 Β· β±οΈ 08.10.2024):
pip install mtcnn -
Conda (π₯ 16K Β· β±οΈ 22.04.2025):
conda install -c conda-forge mtcnn
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GitHub (π¨βπ» 150 Β· π 410 Β· π₯ 24K Β· π¦ 28 Β· π 3.4K - 10% open Β· β±οΈ 24.09.2025):
git clone https://github.com/CellProfiler/CellProfiler -
PyPi (π₯ 1.6K / month Β· π¦ 2 Β· β±οΈ 16.09.2024):
pip install cellprofiler
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GitHub (π¨βπ» 35 Β· π 150 Β· π¦ 1.6K Β· π 92 - 21% open Β· β±οΈ 05.08.2025):
git clone https://github.com/luispedro/mahotas -
PyPi (π₯ 42K / month Β· π¦ 63 Β· β±οΈ 17.07.2024):
pip install mahotas -
Conda (π₯ 790K Β· β±οΈ 21.10.2025):
conda install -c conda-forge mahotas
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GitHub (π¨βπ» 19 Β· π 460 Β· π₯ 29 Β· π¦ 200 Β· π 140 - 25% open Β· β±οΈ 15.08.2025):
git clone https://github.com/idealo/imagededup -
PyPi (π₯ 69K / month Β· π¦ 29 Β· β±οΈ 15.08.2025):
pip install imagededup
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GitHub (π¨βπ» 39 Β· π 370 Β· π 240 - 60% open Β· β±οΈ 03.02.2025):
git clone https://github.com/tensorflow/graphics -
PyPi (π₯ 61K / month Β· π¦ 11 Β· β±οΈ 03.12.2021):
pip install tensorflow-graphics
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GitHub (π¨βπ» 32 Β· π 260 Β· π₯ 360 Β· π¦ 340 Β· π 180 - 16% open Β· β±οΈ 30.04.2025):
git clone https://github.com/tryolabs/norfair -
PyPi (π₯ 44K / month Β· π¦ 9 Β· β±οΈ 30.04.2025):
pip install norfair
-
GitHub (π¨βπ» 17 Β· π 53 Β· π¦ 1.2K Β· π 670 - 29% open Β· β±οΈ 04.09.2025):
git clone https://github.com/libvips/pyvips -
PyPi (π₯ 190K / month Β· π¦ 94 Β· β±οΈ 28.04.2025):
pip install pyvips -
Conda (π₯ 260K Β· β±οΈ 04.09.2025):
conda install -c conda-forge pyvips
-
GitHub (π¨βπ» 59 Β· π 420 Β· π 210 - 50% open Β· β±οΈ 27.10.2025):
git clone https://github.com/facebookresearch/pytorchvideo -
PyPi (π₯ 53K / month Β· π¦ 24 Β· β±οΈ 20.01.2022):
pip install pytorchvideo
-
GitHub (π¨βπ» 120 Β· π 920 Β· π¦ 23 Β· π 690 - 21% open Β· β±οΈ 24.04.2025):
git clone https://github.com/facebookresearch/mmf -
PyPi (π₯ 190 / month Β· π¦ 1 Β· β±οΈ 12.06.2020):
pip install mmf
-
GitHub (π¨βπ» 32 Β· π 250 Β· π¦ 7 Β· π 200 - 35% open Β· β±οΈ 06.05.2025):
git clone https://github.com/google-research/kubric -
PyPi (π₯ 6.6K / month Β· β±οΈ 27.12.2023):
pip install kubric-nightly
-
GitHub (π¨βπ» 41 Β· π 130 Β· π 570 - 10% open Β· β±οΈ 31.10.2024):
git clone https://github.com/airctic/icevision -
PyPi (π₯ 2.3K / month Β· π¦ 6 Β· β±οΈ 10.02.2022):
pip install icevision
-
GitHub (π¨βπ» 35 Β· π 1.2K Β· π¦ 23 Β· π 720 - 59% open Β· β±οΈ 27.10.2025):
git clone https://github.com/facebookresearch/SlowFast -
PyPi (π₯ 22 / month Β· β±οΈ 15.01.2020):
pip install pyslowfast
-
GitHub (π¨βπ» 11 Β· π 760 Β· π 220 - 48% open Β· β±οΈ 18.12.2024):
git clone https://github.com/idealo/image-super-resolution -
PyPi (π₯ 3.9K / month Β· π¦ 5 Β· β±οΈ 08.01.2020):
pip install ISR -
Docker Hub (π₯ 290 Β· β 1 Β· β±οΈ 01.04.2019):
docker pull idealo/image-super-resolution-gpu
-
GitHub (π¨βπ» 8 Β· π 110 Β· π₯ 48 Β· β±οΈ 11.08.2025):
git clone https://github.com/jasmcaus/caer -
PyPi (π₯ 3.8K / month Β· π¦ 3 Β· β±οΈ 11.08.2025):
pip install caer
-
GitHub (π¨βπ» 95 Β· π 460 Β· π 400 - 70% open Β· β±οΈ 06.08.2025):
git clone https://github.com/google-research/scenic
- <b><a href="https://github.com/scikit-image/scikit-image">scikit-image</a></b> (π₯41 Β· β 6.4K Β· π) - Image processing in Python. <code>βUnlicensed</code>
- <b><a href="https://github.com/glfw/glfw">glfw</a></b> (π₯38 Β· β 14K) - A multi-platform library for OpenGL, OpenGL ES, Vulkan, window and input. <code><a href="https://tldrlegal.com/search?q=Zlib">βοΈZlib</a></code>
- <b><a href="https://github.com/open-mmlab/mmdetection">MMDetection</a></b> (π₯37 Β· β 32K Β· π) - 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> (π₯36 Β· β 15K Β· π) - 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> (π₯35 Β· β 56K Β· π) - 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> (π₯31 Β· β 4.6K Β· π) - 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> (π₯30 Β· β 9.6K) - PyTorch3D is FAIRs library of reusable components for.. <code>βUnlicensed</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> (π₯30 Β· β 8.8K Β· π) - 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> (π₯28 Β· β 7.4K Β· π) - 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> (π₯27 Β· β 5.9K Β· π) - 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> (π₯27 Β· β 5.1K Β· π) - 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> (π₯27 Β· β 3.6K Β· π) - 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> (π₯27 Β· β 1.5K Β· π) - 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> (π₯26 Β· β 5K Β· π) - 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> (π₯25 Β· β 2.2K Β· π) - The friendly PIL fork. <code><a href="https://tldrlegal.com/search?q=PIL">βοΈPIL</a></code>
- <b><a href="https://github.com/Layout-Parser/layout-parser">layout-parser</a></b> (π₯24 Β· β 5.6K Β· π) - 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> (π₯24 Β· β 4.9K Β· π) - 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> (π₯23 Β· β 3K Β· π) - 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> (π₯23 Β· β 1.6K Β· π) - 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> (π₯22 Β· β 4.3K Β· π) - 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> (π₯22 Β· β 3.3K Β· π) - 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> (π₯22 Β· β 2.4K Β· π) - 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> (π₯21 Β· β 620 Β· π) - 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> (π₯20 Β· β 15K Β· π) - 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> (π₯20 Β· β 3K Β· π) - 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> (π₯19 Β· 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> (π₯18 Β· β 2.2K Β· π) - 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> (π₯17 Β· β 260 Β· π) - 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> (π₯16 Β· β 920 Β· π) - 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> (π₯14 Β· β 200 Β· π) - HugsVision is a easy to use huggingface wrapper for state-of-.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code>huggingface</code>
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> (π₯46 Β· β 16K) - Network Analysis in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>-
GitHub (π¨βπ» 790 Β· π 3.4K Β· π₯ 110 Β· π¦ 430K Β· π 3.5K - 10% open Β· β±οΈ 29.10.2025):
git clone https://github.com/networkx/networkx -
PyPi (π₯ 130M / month Β· π¦ 12K Β· β±οΈ 29.05.2025):
pip install networkx -
Conda (π₯ 26M Β· β±οΈ 04.06.2025):
conda install -c conda-forge networkx
-
GitHub (π¨βπ» 560 Β· π 3.9K Β· π¦ 11K Β· π 4K - 30% open Β· β±οΈ 29.10.2025):
git clone https://github.com/pyg-team/pytorch_geometric -
PyPi (π₯ 940K / month Β· π¦ 730 Β· β±οΈ 15.10.2025):
pip install torch-geometric -
Conda (π₯ 190K Β· β±οΈ 16.10.2025):
conda install -c conda-forge pytorch_geometric
-
GitHub (π¨βπ» 300 Β· π 3K Β· π¦ 4.1K Β· π 3K - 20% open Β· β±οΈ 31.07.2025):
git clone https://github.com/dmlc/dgl -
PyPi (π₯ 150K / month Β· π¦ 150 Β· β±οΈ 13.05.2024):
pip install dgl
-
GitHub (π¨βπ» 48 Β· π 220 Β· π 420 - 51% open Β· β±οΈ 30.10.2025):
git clone https://github.com/graphistry/pygraphistry -
PyPi (π₯ 8.5K / month Β· π¦ 9 Β· β±οΈ 21.10.2025):
pip install graphistry
-
GitHub (π¨βπ» 32 Β· π 400 Β· π¦ 2.6K Β· π 310 - 11% open Β· β±οΈ 06.05.2025):
git clone https://github.com/snap-stanford/ogb -
PyPi (π₯ 100K / month Β· π¦ 73 Β· β±οΈ 07.04.2023):
pip install ogb -
Conda (π₯ 63K Β· β±οΈ 22.04.2025):
conda install -c conda-forge ogb
-
GitHub (π¨βπ» 43 Β· π 210 Β· π₯ 240 Β· π¦ 350 Β· π 590 - 20% open Β· β±οΈ 18.07.2025):
git clone https://github.com/pykeen/pykeen -
PyPi (π₯ 31K / month Β· π¦ 28 Β· β±οΈ 24.04.2025):
pip install pykeen
-
GitHub (π¨βπ» 39 Β· π 400 Β· π 210 - 18% open Β· β±οΈ 18.09.2025):
git clone https://github.com/benedekrozemberczki/pytorch_geometric_temporal -
PyPi (π₯ 6.7K / month Β· π¦ 12 Β· β±οΈ 16.07.2025):
pip install torch-geometric-temporal
-
GitHub (π¨βπ» 40 Β· π 150 Β· π 190 - 16% open Β· β±οΈ 12.08.2025):
git clone https://github.com/rusty1s/pytorch_cluster -
PyPi (π₯ 34K / month Β· π¦ 62 Β· β±οΈ 12.10.2023):
pip install torch-cluster -
Conda (π₯ 440K Β· β±οΈ 22.09.2025):
conda install -c conda-forge pytorch_cluster
- <b><a href="https://github.com/igraph/python-igraph">igraph</a></b> (π₯34 Β· β 1.4K) - Python interface for igraph. <code><a href="http://bit.ly/2KucAZR">βοΈGPL-2.0</a></code>
- <b><a href="https://github.com/danielegrattarola/spektral">Spektral</a></b> (π₯28 Β· β 2.4K Β· π) - 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> (π₯27 Β· β 3K Β· π) - 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> (π₯26 Β· β 2.7K Β· π) - PYthon svg GrAph plotting Library. <code><a href="http://bit.ly/37RvQcA">βοΈLGPL-3.0</a></code>
- <b><a href="https://github.com/PaddlePaddle/PGL">Paddle Graph Learning</a></b> (π₯26 Β· β 1.6K Β· π) - 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> (π₯25 Β· β 2.2K Β· π) - 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> (π₯25 Β· β 1.3K Β· π) - 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> (π₯24 Β· β 2.3K Β· π) - Karate Club: An API Oriented Open-source Python Framework.. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/google-deepmind/graph_nets">graph-nets</a></b> (π₯22 Β· β 5.4K Β· π) - 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> (π₯21 Β· β 3.4K Β· π) - 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> (π₯21 Β· β 1.7K Β· π) - 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> (π₯21 Β· β 1.5K Β· π) - 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> (π₯20 Β· β 2.7K Β· π) - DeepWalk - Deep Learning for Graphs. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/divelab/DIG">DIG</a></b> (π₯20 Β· β 2K Β· π) - A library for graph deep learning research. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/snap-stanford/deepsnap">deepsnap</a></b> (π₯20 Β· β 560 Β· π) - 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> (π₯20 Β· β 260 Β· π) - 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> (π₯17 Β· β 1.8K Β· π) - 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> (π₯17 Β· β 440 Β· π) - 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> (π₯17 Β· β 320) - Analyze Data with Pandas-based Networks. Documentation:. <code>βUnlicensed</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> (π₯16 Β· β 1.1K Β· π) - 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> (π₯16 Β· β 550 Β· π) - 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> (π₯16 Β· β 380 Β· π) - 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> (π₯15 Β· β 2.9K Β· π) - 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> (π₯14 Β· β 3.8K Β· π) - 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> (π₯14 Β· β 3.6K Β· π) - 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> (π₯14 Β· β 1.7K Β· π) - 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> (π₯14 Β· β 1.3K Β· π) - 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> (π₯13 Β· β 4K Β· π) - An Open-Source Package for Knowledge Embedding (KE). <code>βUnlicensed</code>
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> (π₯38 Β· 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 (π¨βπ» 260 Β· π 1.5K Β· π¦ 3.9K Β· π 1.2K - 12% open Β· β±οΈ 30.10.2025):
git clone https://github.com/speechbrain/speechbrain -
PyPi (π₯ 1.1M / month Β· π¦ 79 Β· β±οΈ 07.04.2025):
pip install speechbrain
-
GitHub (π¨βπ» 520 Β· π 2.3K Β· π₯ 84 Β· π¦ 480 Β· π 2.5K - 3% open Β· β±οΈ 30.10.2025):
git clone https://github.com/espnet/espnet -
PyPi (π₯ 24K / month Β· π¦ 19 Β· β±οΈ 13.09.2025):
pip install espnet
-
GitHub (π¨βπ» 240 Β· π 730 Β· π 1.1K - 31% open Β· β±οΈ 29.10.2025):
git clone https://github.com/pytorch/audio -
PyPi (π₯ 15M / month Β· π¦ 2.4K Β· β±οΈ 15.10.2025):
pip install torchaudio
-
GitHub (π¨βπ» 56 Β· π 2.4K Β· π¦ 21 Β· π 670 - 48% open Β· β±οΈ 28.10.2025):
git clone https://github.com/Uberi/speech_recognition -
PyPi (π₯ 2.2M / month Β· π¦ 730 Β· β±οΈ 12.05.2025):
pip install SpeechRecognition -
Conda (π₯ 360K Β· β±οΈ 12.05.2025):
conda install -c conda-forge speechrecognition
-
GitHub (π¨βπ» 130 Β· π 1K Β· π 1.3K - 5% open Β· β±οΈ 19.05.2025):
git clone https://github.com/librosa/librosa -
PyPi (π₯ 5.6M / month Β· π¦ 1.6K Β· β±οΈ 11.03.2025):
pip install librosa -
Conda (π₯ 1.1M Β· β±οΈ 22.04.2025):
conda install -c conda-forge librosa
-
GitHub (π¨βπ» 160 Β· π 4.1K Β· π₯ 660K Β· π¦ 540 Β· π 2.1K - 7% open Β· β±οΈ 19.06.2025):
git clone https://github.com/mozilla/DeepSpeech -
PyPi (π₯ 5.5K / month Β· π¦ 24 Β· β±οΈ 19.12.2020):
pip install deepspeech -
Conda (π₯ 4.2K Β· β±οΈ 22.04.2025):
conda install -c conda-forge deepspeech
-
GitHub (π¨βπ» 27 Β· π 110 Β· π¦ 35K Β· π 98 - 40% open Β· β±οΈ 26.10.2025):
git clone https://github.com/beetbox/audioread -
PyPi (π₯ 4.8M / month Β· π¦ 180 Β· β±οΈ 26.10.2025):
pip install audioread -
Conda (π₯ 1.2M Β· β±οΈ 02.10.2025):
conda install -c conda-forge audioread
-
GitHub (π¨βπ» 22 Β· π 3K Β· π₯ 4.4M Β· π¦ 1.1K Β· π 830 - 32% open Β· β±οΈ 02.04.2025):
git clone https://github.com/deezer/spleeter -
PyPi (π₯ 26K / month Β· π¦ 18 Β· β±οΈ 03.04.2025):
pip install spleeter -
Conda (π₯ 120K Β· β±οΈ 22.04.2025):
conda install -c conda-forge spleeter
-
GitHub (π¨βπ» 34 Β· π 200 Β· π¦ 840 Β· π 210 - 26% open Β· β±οΈ 26.09.2025):
git clone https://github.com/iver56/audiomentations -
PyPi (π₯ 110K / month Β· π¦ 38 Β· β±οΈ 13.09.2025):
pip install audiomentations
-
GitHub (π¨βπ» 200 Β· π 240 Β· π₯ 3.8K Β· π¦ 760 Β· π 160 - 14% open Β· β±οΈ 16.10.2025):
git clone https://github.com/idiap/coqui-ai-TTS -
PyPi (π₯ 94K / month Β· π¦ 34 Β· β±οΈ 25.09.2025):
pip install coqui-tts
-
GitHub (π¨βπ» 160 Β· π 3.7K Β· π¦ 600 Β· π 1K - 41% open Β· β±οΈ 08.07.2025):
git clone https://github.com/magenta/magenta -
PyPi (π₯ 4.8K / month Β· π¦ 5 Β· β±οΈ 01.08.2022):
pip install magenta
-
GitHub (π¨βπ» 43 Β· π 550 Β· π¦ 51 Β· π 600 - 0% open Β· β±οΈ 17.10.2025):
git clone https://github.com/Picovoice/Porcupine -
PyPi (π₯ 25K / month Β· π¦ 38 Β· β±οΈ 05.02.2025):
pip install pvporcupine
-
GitHub (π¨βπ» 28 Β· π 1.2K Β· π¦ 670 Β· π 330 - 62% open Β· β±οΈ 04.08.2025):
git clone https://github.com/tyiannak/pyAudioAnalysis -
PyPi (π₯ 24K / month Β· π¦ 12 Β· β±οΈ 07.02.2022):
pip install pyAudioAnalysis
-
GitHub (π¨βπ» 38 Β· π 120 Β· π₯ 21K Β· π 260 - 46% open Β· β±οΈ 28.04.2025):
git clone https://github.com/bastibe/python-soundfile -
PyPi (π₯ 9.5M / month Β· π¦ 1.1K Β· β±οΈ 25.01.2025):
pip install soundfile -
conda install -c anaconda pysoundfile
-
GitHub (π¨βπ» 27 Β· π 100 Β· π¦ 1.3K Β· π 120 - 4% open Β· β±οΈ 13.08.2025):
git clone https://github.com/devsnd/tinytag -
PyPi (π₯ 120K / month Β· π¦ 130 Β· β±οΈ 13.08.2025):
pip install tinytag
-
GitHub (π¨βπ» 13 Β· π 150 Β· π₯ 33 Β· π¦ 2.5K Β· π 99 - 17% open Β· β±οΈ 26.10.2025):
git clone https://github.com/keunwoochoi/kapre -
PyPi (π₯ 3.2K / month Β· π¦ 11 Β· β±οΈ 26.10.2025):
pip install kapre
-
GitHub (π¨βπ» 16 Β· π 96 Β· π¦ 410 Β· π 65 - 30% open Β· β±οΈ 16.05.2025):
git clone https://github.com/KinWaiCheuk/nnAudio -
PyPi (π₯ 59K / month Β· π¦ 4 Β· β±οΈ 13.02.2024):
pip install nnAudio
-
GitHub (π¨βπ» 3 Β· π 26 Β· π 12 - 16% open Β· β±οΈ 17.02.2025):
git clone https://github.com/adefossez/julius -
PyPi (π₯ 840K / month Β· π¦ 44 Β· β±οΈ 20.09.2022):
pip install julius
- <b><a href="https://github.com/jiaaro/pydub">Pydub</a></b> (π₯36 Β· β 9.6K Β· π) - 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> (π₯27 Β· β 3.5K) - a library for audio and music analysis. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/MTG/essentia">Essentia</a></b> (π₯27 Β· β 3.3K) - C++ library for audio and music analysis, description and.. <code><a href="http://bit.ly/3pwmjO5">βοΈAGPL-3.0</a></code>
- <b><a href="https://github.com/CPJKU/madmom">Madmom</a></b> (π₯27 Β· β 1.5K Β· π) - 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> (π₯26 Β· β 10K Β· π) - 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> (π₯26 Β· β 2.4K Β· π) - 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> (π₯25 Β· β 3.1K Β· π) - 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> (π₯23 Β· β 6.7K Β· π) - 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> (π₯21 Β· β 390 Β· π€) - scalable audio processing framework and server written in.. <code><a href="http://bit.ly/3pwmjO5">βοΈAGPL-3.0</a></code>
- <b><a href="https://github.com/bmcfee/muda">Muda</a></b> (π₯18 Β· β 240 Β· π) - 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> (π₯10 Β· β 550 Β· π) - 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>
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> (π₯43 Β· 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 (π¨βπ» 310 Β· π 2.2K Β· π¦ 9.2K Β· π 3.3K - 13% open Β· β±οΈ 29.10.2025):
git clone https://github.com/visgl/deck.gl -
PyPi (π₯ 16M / month Β· π¦ 160 Β· β±οΈ 21.03.2025):
pip install pydeck -
Conda (π₯ 850K Β· β±οΈ 22.04.2025):
conda install -c conda-forge pydeck -
npm (π₯ 750K / month Β· π¦ 360 Β· β±οΈ 16.10.2025):
npm install deck.gl
-
GitHub (π¨βπ» 180 Β· π 2.2K Β· π¦ 65K Β· π 1.2K - 6% open Β· β±οΈ 06.10.2025):
git clone https://github.com/python-visualization/folium -
PyPi (π₯ 2.8M / month Β· π¦ 1K Β· β±οΈ 16.06.2025):
pip install folium -
Conda (π₯ 4.4M Β· β±οΈ 16.06.2025):
conda install -c conda-forge folium
-
GitHub (π¨βπ» 170 Β· π 600 Β· π₯ 4K Β· π¦ 110K Β· π 1.3K - 18% open Β· β±οΈ 28.10.2025):
git clone https://github.com/shapely/shapely -
PyPi (π₯ 62M / month Β· π¦ 4.7K Β· β±οΈ 24.09.2025):
pip install shapely -
Conda (π₯ 14M Β· β±οΈ 28.10.2025):
conda install -c conda-forge shapely
-
GitHub (π¨βπ» 250 Β· π 980 Β· π₯ 3.1K Β· π¦ 60K Β· π 1.8K - 24% open Β· β±οΈ 25.10.2025):
git clone https://github.com/geopandas/geopandas -
PyPi (π₯ 11M / month Β· π¦ 3.8K Β· β±οΈ 26.06.2025):
pip install geopandas -
Conda (π₯ 5.4M Β· β±οΈ 06.10.2025):
conda install -c conda-forge geopandas
-
GitHub (π¨βπ» 170 Β· π 540 Β· π₯ 1K Β· π¦ 19K Β· π 1.9K - 8% open Β· β±οΈ 26.09.2025):
git clone https://github.com/rasterio/rasterio -
PyPi (π₯ 2.8M / month Β· π¦ 1.5K Β· β±οΈ 02.12.2024):
pip install rasterio -
Conda (π₯ 5.3M Β· β±οΈ 17.09.2025):
conda install -c conda-forge rasterio
-
GitHub (π¨βπ» 74 Β· π 230 Β· π¦ 47K Β· π 660 - 6% open Β· β±οΈ 29.10.2025):
git clone https://github.com/pyproj4/pyproj -
PyPi (π₯ 14M / month Β· π¦ 2.3K Β· β±οΈ 14.08.2025):
pip install pyproj -
Conda (π₯ 12M Β· β±οΈ 15.09.2025):
conda install -c conda-forge pyproj
-
GitHub (π¨βπ» 99 Β· π 1.1K Β· π₯ 16K Β· π¦ 1K Β· π 920 - 8% open Β· β±οΈ 28.10.2025):
git clone https://github.com/Esri/arcgis-python-api -
PyPi (π₯ 150K / month Β· π¦ 44 Β· β±οΈ 27.10.2025):
pip install arcgis -
docker pull esridocker/arcgis-api-python-notebook
-
GitHub (π¨βπ» 78 Β· π 210 Β· π¦ 27K Β· π 820 - 5% open Β· β±οΈ 20.02.2025):
git clone https://github.com/Toblerity/Fiona -
PyPi (π₯ 5.6M / month Β· π¦ 380 Β· β±οΈ 16.09.2024):
pip install fiona -
Conda (π₯ 7.9M Β· β±οΈ 22.04.2025):
conda install -c conda-forge fiona
-
GitHub (π¨βπ» 94 Β· π 360 Β· π¦ 18K Β· π 660 - 44% open Β· β±οΈ 19.06.2025):
git clone https://github.com/jupyter-widgets/ipyleaflet -
PyPi (π₯ 230K / month Β· π¦ 340 Β· β±οΈ 13.06.2025):
pip install ipyleaflet -
Conda (π₯ 1.8M Β· β±οΈ 13.06.2025):
conda install -c conda-forge ipyleaflet -
npm (π₯ 2.7K / month Β· π¦ 9 Β· β±οΈ 13.06.2025):
npm install jupyter-leaflet
-
GitHub (π¨βπ» 58 Β· π 120 Β· π¦ 21K Β· π 100 - 26% open Β· β±οΈ 21.12.2024):
git clone https://github.com/jazzband/geojson -
PyPi (π₯ 3.6M / month Β· π¦ 720 Β· β±οΈ 21.12.2024):
pip install geojson -
Conda (π₯ 1.1M Β· β±οΈ 22.04.2025):
conda install -c conda-forge geojson
-
GitHub (π¨βπ» 79 Β· π 310 Β· π¦ 1.8K Β· π 660 - 3% open Β· β±οΈ 08.09.2025):
git clone https://github.com/pysal/pysal -
PyPi (π₯ 42K / month Β· π¦ 65 Β· β±οΈ 31.07.2025):
pip install pysal -
Conda (π₯ 730K Β· β±οΈ 01.08.2025):
conda install -c conda-forge pysal
-
GitHub (π¨βπ» 34 Β· π 79 Β· π¦ 5 Β· π 360 - 31% open Β· β±οΈ 29.10.2025):
git clone https://github.com/holoviz/geoviews -
PyPi (π₯ 69K / month Β· π¦ 76 Β· β±οΈ 14.08.2025):
pip install geoviews -
Conda (π₯ 340K Β· β±οΈ 14.08.2025):
conda install -c conda-forge geoviews
-
GitHub (π¨βπ» 44 Β· π 160 Β· π₯ 75 Β· π¦ 440 Β· π 250 - 16% open Β· β±οΈ 31.07.2025):
git clone https://github.com/earthlab/earthpy -
PyPi (π₯ 14K / month Β· π¦ 17 Β· β±οΈ 01.10.2021):
pip install earthpy -
Conda (π₯ 98K Β· β±οΈ 22.04.2025):
conda install -c conda-forge earthpy
-
GitHub (π¨βπ» 19 Β· π 87 Β· π¦ 540 Β· π 59 - 8% open Β· β±οΈ 08.07.2025):
git clone https://github.com/geospace-code/pymap3d -
PyPi (π₯ 490K / month Β· π¦ 50 Β· β±οΈ 08.07.2025):
pip install pymap3d -
Conda (π₯ 120K Β· β±οΈ 08.07.2025):
conda install -c conda-forge pymap3d
-
GitHub (π¨βπ» 23 Β· π 140 Β· π 110 - 38% open Β· β±οΈ 06.02.2025):
git clone https://github.com/mapbox/mapboxgl-jupyter -
PyPi (π₯ 10K / month Β· π¦ 12 Β· β±οΈ 02.06.2019):
pip install mapboxgl
- <b><a href="https://github.com/pytroll/satpy">Satpy</a></b> (π₯34 Β· β 1.1K) - Python package for earth-observing satellite data processing. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/geopy/geopy">geopy</a></b> (π₯32 Β· β 4.7K Β· π) - 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> (π₯32 Β· β 1.6K Β· π) - Python Geocoder. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/marceloprates/prettymaps">prettymaps</a></b> (π₯24 Β· β 12K) - Draw pretty maps from OpenStreetMap data! Built with osmnx.. <code><a href="http://bit.ly/3pwmjO5">βοΈAGPL-3.0</a></code>
- <b><a href="https://github.com/sentinelsat/sentinelsat">Sentinelsat</a></b> (π₯24 Β· β 1K Β· π) - Search and download Copernicus Sentinel satellite images. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/pbugnion/gmaps">gmaps</a></b> (π₯22 Β· β 760 Β· π) - 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> (π₯21 Β· β 1K Β· π) - python toolbox for visualizing geographical data and making maps. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
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> (π₯42 Β· β 20K) - Download market data from Yahoo! Finances API. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>-
GitHub (π¨βπ» 140 Β· π 2.8K Β· π¦ 86K Β· π 1.7K - 9% open Β· β±οΈ 18.09.2025):
git clone https://github.com/ranaroussi/yfinance -
PyPi (π₯ 5.9M / month Β· π¦ 1.2K Β· β±οΈ 17.09.2025):
pip install yfinance -
Conda (π₯ 99K Β· β±οΈ 25.03.2025):
conda install -c ranaroussi yfinance
-
GitHub (π¨βπ» 140 Β· π 5K Β· π₯ 910 Β· π¦ 21 Β· π 1K - 28% open Β· β±οΈ 17.10.2025):
git clone https://github.com/microsoft/qlib -
PyPi (π₯ 16K / month Β· π¦ 3 Β· β±οΈ 15.08.2025):
pip install pyqlib
-
GitHub (π¨βπ» 35 Β· π 450 Β· π¦ 1.7K Β· π 350 - 23% open Β· β±οΈ 27.10.2025):
git clone https://github.com/pmorissette/bt -
PyPi (π₯ 11K / month Β· π¦ 15 Β· β±οΈ 12.04.2025):
pip install bt -
Conda (π₯ 110K Β· β±οΈ 02.10.2025):
conda install -c conda-forge bt
-
GitHub (π¨βπ» 44 Β· π 760 Β· π 290 - 0% open Β· β±οΈ 27.07.2025):
git clone https://github.com/RomelTorres/alpha_vantage -
PyPi (π₯ 140K / month Β· π¦ 35 Β· β±οΈ 18.07.2024):
pip install alpha_vantage -
Conda (π₯ 10K Β· β±οΈ 22.04.2025):
conda install -c conda-forge alpha_vantage
-
GitHub (π¨βπ» 36 Β· π 330 Β· π¦ 580 Β· π 140 - 17% open Β· β±οΈ 27.10.2025):
git clone https://github.com/pmorissette/ffn -
PyPi (π₯ 25K / month Β· π¦ 22 Β· β±οΈ 11.02.2025):
pip install ffn -
Conda (π₯ 26K Β· β±οΈ 22.04.2025):
conda install -c conda-forge ffn
-
GitHub (π¨βπ» 10 Β· π 310 Β· π¦ 1.3K Β· π 130 - 10% open Β· β±οΈ 18.05.2025):
git clone https://github.com/jealous/stockstats -
PyPi (π₯ 51K / month Β· π¦ 14 Β· β±οΈ 18.05.2025):
pip install stockstats
-
GitHub (π¨βπ» 48 Β· π 630 Β· π 65 - 56% open Β· β±οΈ 21.03.2025):
git clone https://github.com/google/tf-quant-finance -
PyPi (π₯ 410 / month Β· π¦ 3 Β· β±οΈ 19.08.2022):
pip install tf-quant-finance
-
GitHub (π¨βπ» 19 Β· π 510 Β· π₯ 57 Β· π¦ 16 Β· π 35 - 88% open Β· β±οΈ 10.03.2025):
git clone https://github.com/cuemacro/finmarketpy -
PyPi (π₯ 340 / month Β· β±οΈ 10.03.2025):
pip install finmarketpy
- <b><a href="https://github.com/bashtage/arch">arch</a></b> (π₯33 Β· β 1.5K) - ARCH models in Python. <code>βUnlicensed</code>
- <b><a href="https://github.com/quantopian/zipline">zipline</a></b> (π₯32 Β· β 19K Β· π) - 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> (π₯32 Β· β 4.8K Β· π) - 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> (π₯31 Β· β 6.1K Β· π) - 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> (π₯29 Β· β 19K Β· π) - Python Backtesting library for trading strategies. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/erdewit/ib_insync">IB-insync</a></b> (π₯28 Β· β 3.1K Β· π) - 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> (π₯27 Β· β 4K Β· π) - 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> (π₯27 Β· β 2.5K Β· π) - 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> (π₯27 Β· β 1.4K Β· π) - 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> (π₯26 Β· β 7.4K) - Backtest trading strategies in Python. <code><a href="http://bit.ly/3pwmjO5">βοΈAGPL-3.0</a></code>
- <b><a href="https://github.com/tensortrade-org/tensortrade">TensorTrade</a></b> (π₯26 Β· β 5.6K Β· π) - 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> (π₯25 Β· β 4.6K Β· π) - 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> (π₯24 Β· β 2.2K Β· π) - Common financial technical indicators implemented in Pandas. <code><a href="http://bit.ly/37RvQcA">βοΈLGPL-3.0</a></code>
- <b><a href="https://github.com/CryptoSignal/Crypto-Signal">Crypto Signals</a></b> (π₯22 Β· β 5.4K Β· π) - 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> (π₯22 Β· β 1.6K Β· π) - 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> (π₯12 Β· β 1.8K Β· π) - Find big moving stocks before they move using machine.. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/alvarobartt/pyrtfolio">pyrtfolio</a></b> (π₯9 Β· β 150 Β· π) - Python package to generate stock portfolios. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
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> (π₯41 Β· 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 (π¨βπ» 520 Β· π 1.7K Β· π₯ 110 Β· π¦ 4.7K Β· π 3.1K - 39% open Β· β±οΈ 28.10.2025):
git clone https://github.com/alan-turing-institute/sktime -
PyPi (π₯ 1M / month Β· π¦ 160 Β· β±οΈ 25.09.2025):
pip install sktime -
Conda (π₯ 1.2M Β· β±οΈ 18.09.2025):
conda install -c conda-forge sktime-all-extras
-
GitHub (π¨βπ» 190 Β· π 4.6K Β· π₯ 3.2K Β· π¦ 21 Β· π 2.2K - 20% open Β· β±οΈ 21.10.2025):
git clone https://github.com/facebook/prophet -
PyPi (π₯ 84K / month Β· π¦ 91 Β· β±οΈ 05.09.2020):
pip install fbprophet -
Conda (π₯ 1.5M Β· β±οΈ 22.10.2025):
conda install -c conda-forge prophet
-
GitHub (π¨βπ» 56 Β· π 340 Β· π¦ 2K Β· π 400 - 34% open Β· β±οΈ 29.10.2025):
git clone https://github.com/Nixtla/statsforecast -
PyPi (π₯ 990K / month Β· π¦ 91 Β· β±οΈ 29.10.2025):
pip install statsforecast -
Conda (π₯ 220K Β· β±οΈ 30.10.2025):
conda install -c conda-forge statsforecast
-
GitHub (π¨βπ» 46 Β· π 350 Β· π¦ 1.9K Β· π 380 - 38% open Β· β±οΈ 27.10.2025):
git clone https://github.com/tslearn-team/tslearn -
PyPi (π₯ 400K / month Β· π¦ 110 Β· β±οΈ 02.07.2025):
pip install tslearn -
Conda (π₯ 1.7M Β· β±οΈ 03.07.2025):
conda install -c conda-forge tslearn
-
GitHub (π¨βπ» 23 Β· π 170 Β· π¦ 490 Β· π 210 - 8% open Β· β±οΈ 22.09.2025):
git clone https://github.com/JoaquinAmatRodrigo/skforecast -
PyPi (π₯ 96K / month Β· π¦ 18 Β· β±οΈ 22.09.2025):
pip install skforecast
-
GitHub (π¨βπ» 140 Β· π 970 Β· π 1.8K - 13% open Β· β±οΈ 26.10.2025):
git clone https://github.com/unit8co/darts -
PyPi (π₯ 86K / month Β· π¦ 10 Β· β±οΈ 03.10.2025):
pip install u8darts -
Conda (π₯ 94K Β· β±οΈ 05.10.2025):
conda install -c conda-forge u8darts-all -
Docker Hub (π₯ 2.1K Β· β±οΈ 03.10.2025):
docker pull unit8/darts
-
GitHub (π¨βπ» 79 Β· π 710 Β· π¦ 670 Β· π 920 - 59% open Β· β±οΈ 19.10.2025):
git clone https://github.com/jdb78/pytorch-forecasting -
PyPi (π₯ 270K / month Β· π¦ 27 Β· β±οΈ 10.10.2025):
pip install pytorch-forecasting -
Conda (π₯ 87K Β· β±οΈ 05.07.2025):
conda install -c conda-forge pytorch-forecasting
-
GitHub (π¨βπ» 23 Β· π 250 Β· π¦ 13K Β· π 340 - 19% open Β· β±οΈ 07.11.2024):
git clone https://github.com/alkaline-ml/pmdarima -
PyPi (π₯ 7.5M / month Β· π¦ 150 Β· β±οΈ 23.10.2023):
pip install pmdarima -
Conda (π₯ 1.4M Β· β±οΈ 22.04.2025):
conda install -c conda-forge pmdarima
-
GitHub (π¨βπ» 100 Β· π 1.3K Β· π¦ 21 Β· π 550 - 12% open Β· β±οΈ 30.08.2025):
git clone https://github.com/blue-yonder/tsfresh -
PyPi (π₯ 340K / month Β· π¦ 120 Β· β±οΈ 30.08.2025):
pip install tsfresh -
Conda (π₯ 1.5M Β· β±οΈ 31.08.2025):
conda install -c conda-forge tsfresh
-
GitHub (π¨βπ» 41 Β· π 340 Β· π¦ 1.6K Β· π 540 - 13% open Β· β±οΈ 02.09.2025):
git clone https://github.com/TDAmeritrade/stumpy -
PyPi (π₯ 380K / month Β· π¦ 30 Β· β±οΈ 09.07.2024):
pip install stumpy -
Conda (π₯ 1.1M Β· β±οΈ 22.04.2025):
conda install -c conda-forge stumpy
-
GitHub (π¨βπ» 55 Β· π 450 Β· π 650 - 17% open Β· β±οΈ 01.10.2025):
git clone https://github.com/Nixtla/neuralforecast -
PyPi (π₯ 160K / month Β· π¦ 30 Β· β±οΈ 01.10.2025):
pip install neuralforecast -
Conda (π₯ 47K Β· β±οΈ 06.10.2025):
conda install -c conda-forge neuralforecast
-
GitHub (π¨βπ» 120 Β· π 790 Β· π 970 - 34% open Β· β±οΈ 14.08.2025):
git clone https://github.com/awslabs/gluon-ts -
PyPi (π₯ 1.9M / month Β· π¦ 41 Β· β±οΈ 27.06.2025):
pip install gluonts -
Conda (π₯ 3.2K Β· β±οΈ 22.04.2025):
conda install -c anaconda gluonts
-
GitHub (π¨βπ» 49 Β· π 150 Β· π¦ 570 Β· π 270 - 44% open Β· β±οΈ 22.11.2024):
git clone https://github.com/python-streamz/streamz -
PyPi (π₯ 26K / month Β· π¦ 57 Β· β±οΈ 27.07.2022):
pip install streamz -
Conda (π₯ 2.9M Β· β±οΈ 22.04.2025):
conda install -c conda-forge streamz
-
GitHub (π¨βπ» 15 Β· π 180 Β· π¦ 900 Β· π 88 - 59% open Β· β±οΈ 18.06.2025):
git clone https://github.com/johannfaouzi/pyts -
PyPi (π₯ 190K / month Β· π¦ 45 Β· β±οΈ 18.06.2023):
pip install pyts -
Conda (π₯ 35K Β· β±οΈ 22.04.2025):
conda install -c conda-forge pyts
-
GitHub (π¨βπ» 21 Β· π 150 Β· π¦ 220 Β· π 87 - 5% open Β· β±οΈ 20.08.2025):
git clone https://github.com/fraunhoferportugal/tsfel -
PyPi (π₯ 9.4K / month Β· π¦ 14 Β· β±οΈ 20.08.2025):
pip install tsfel
-
GitHub (π¨βπ» 10 Β· π 110 Β· π₯ 39 Β· π¦ 47 Β· π 110 - 11% open Β· β±οΈ 20.02.2025):
git clone https://github.com/linkedin/greykite -
PyPi (π₯ 11K / month Β· β±οΈ 20.02.2025):
pip install greykite
- <b><a href="https://github.com/ourownstory/neural_prophet">NeuralProphet</a></b> (π₯26 Β· β 4.2K Β· π) - 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> (π₯25 Β· β 2.1K Β· π) - 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> (π₯22 Β· β 1.2K Β· π) - 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> (π₯22 Β· β 1.2K Β· π) - 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> (π₯21 Β· β 580 Β· π) - 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> (π₯21 Β· β 480 Β· π) - 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> (π₯20 Β· β 520 Β· π) - 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> (π₯19 Β· β 740 Β· π) - 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> (π₯19 Β· β 430 Β· π) - 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> (π₯17 Β· β 760 Β· π) - 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> (π₯15 Β· β 360 Β· π) - 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> (π₯14 Β· β 520 Β· π) - 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> (π₯8 Β· β 71 Β· π) - A library for Time Series EDA (exploratory data analysis). <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
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> (π₯38 Β· 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 (π¨βπ» 260 Β· π 610 Β· π₯ 410 Β· π¦ 4.4K Β· π 2.4K - 12% open Β· β±οΈ 30.10.2025):
git clone https://github.com/nilearn/nilearn -
PyPi (π₯ 270K / month Β· π¦ 350 Β· β±οΈ 03.09.2025):
pip install nilearn -
Conda (π₯ 400K Β· β±οΈ 04.09.2025):
conda install -c conda-forge nilearn
-
GitHub (π¨βπ» 240 Β· π 1.3K Β· π¦ 4.5K Β· π 3.3K - 14% open Β· β±οΈ 10.10.2025):
git clone https://github.com/Project-MONAI/MONAI -
PyPi (π₯ 320K / month Β· π¦ 200 Β· β±οΈ 22.09.2025):
pip install monai -
Conda (π₯ 60K Β· β±οΈ 22.09.2025):
conda install -c conda-forge monai
-
GitHub (π¨βπ» 410 Β· π 1.4K Β· π 5.1K - 11% open Β· β±οΈ 29.10.2025):
git clone https://github.com/mne-tools/mne-python -
PyPi (π₯ 280K / month Β· π¦ 530 Β· β±οΈ 14.10.2025):
pip install mne -
Conda (π₯ 620K Β· β±οΈ 14.10.2025):
conda install -c conda-forge mne
-
GitHub (π¨βπ» 100 Β· π 260 Β· π¦ 170 Β· π 2.6K - 11% open Β· β±οΈ 29.10.2025):
git clone https://github.com/hail-is/hail -
PyPi (π₯ 110K / month Β· π¦ 44 Β· β±οΈ 09.09.2025):
pip install hail
-
GitHub (π¨βπ» 110 Β· π 260 Β· π¦ 30K Β· π 550 - 23% open Β· β±οΈ 21.10.2025):
git clone https://github.com/nipy/nibabel -
PyPi (π₯ 910K / month Β· π¦ 1.2K Β· β±οΈ 23.10.2024):
pip install nibabel -
Conda (π₯ 1M Β· β±οΈ 22.04.2025):
conda install -c conda-forge nibabel
-
GitHub (π¨βπ» 260 Β· π 530 Β· π¦ 7.2K Β· π 1.4K - 30% open Β· β±οΈ 28.04.2025):
git clone https://github.com/nipy/nipype -
PyPi (π₯ 360K / month Β· π¦ 150 Β· β±οΈ 19.03.2025):
pip install nipype -
Conda (π₯ 990K Β· β±οΈ 05.05.2025):
conda install -c conda-forge nipype
-
GitHub (π¨βπ» 120 Β· π 560 Β· π¦ 4.2K Β· π 980 - 27% open Β· β±οΈ 29.10.2024):
git clone https://github.com/CamDavidsonPilon/lifelines -
PyPi (π₯ 1.5M / month Β· π¦ 160 Β· β±οΈ 29.10.2024):
pip install lifelines -
Conda (π₯ 500K Β· β±οΈ 22.04.2025):
conda install -c conda-forge lifelines
-
GitHub (π¨βπ» 41 Β· π 760 Β· π₯ 4.9K Β· π¦ 4 Β· π 960 - 0% open Β· β±οΈ 10.09.2025):
git clone https://github.com/google/deepvariant -
Conda (π₯ 79K Β· β±οΈ 24.05.2025):
conda install -c bioconda deepvariant
-
GitHub (π¨βπ» 35 Β· π 140 Β· π 230 - 38% open Β· β±οΈ 06.01.2025):
git clone https://github.com/brainiak/brainiak -
PyPi (π₯ 1.3K / month Β· β±οΈ 07.01.2025):
pip install brainiak -
Docker Hub (π₯ 2K Β· β 1 Β· β±οΈ 07.01.2025):
docker pull brainiak/brainiak
- <b><a href="https://github.com/dipy/dipy">DIPY</a></b> (π₯31 Β· β 790) - DIPY is the paragon 3D/4D+ medical imaging library in Python... <code>βUnlicensed</code>
- <b><a href="https://github.com/NifTK/NiftyNet">NiftyNet</a></b> (π₯24 Β· β 1.4K Β· π) - [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> (π₯24 Β· β 400 Β· π€) - Neuroimaging in Python FMRI analysis package. <code>βUnlicensed</code>
- <b><a href="https://github.com/loli/medpy">MedPy</a></b> (π₯23 Β· β 610 Β· π) - Medical image processing in Python. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/DLTK/DLTK">DLTK</a></b> (π₯20 Β· β 1.4K Β· π) - 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> (π₯19 Β· β 290 Β· π€) - 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> (π₯17 Β· β 870 Β· π) - 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> (π₯14 Β· β 1.3K Β· π) - 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> (π₯14 Β· β 130 Β· π) - 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> (π₯12 Β· β 2.1K Β· π) - Many studies have shown that the performance on deep learning is.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
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> (π₯30 Β· 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 (π¨βπ» 82 Β· π 170 Β· π¦ 100 Β· π 580 - 21% open Β· β±οΈ 30.10.2025):
git clone https://github.com/skrub-data/skrub -
PyPi (π₯ 45K / month Β· π¦ 20 Β· β±οΈ 25.09.2025):
pip install skrub
-
GitHub (π¨βπ» 27 Β· π 160 Β· π₯ 64 Β· π 180 - 5% open Β· β±οΈ 19.04.2025):
git clone https://github.com/manujosephv/pytorch_tabular -
PyPi (π₯ 5.5K / month Β· π¦ 9 Β· β±οΈ 28.11.2024):
pip install pytorch_tabular
-
GitHub (π¨βπ» 14 Β· π 25 Β· π¦ 9 Β· β±οΈ 28.10.2025):
git clone https://github.com/upgini/upgini -
PyPi (π₯ 5.9K / month Β· β±οΈ 28.10.2025):
pip install upgini
- <b><a href="https://github.com/AnotherSamWilson/miceforest">miceforest</a></b> (π₯21 Β· β 390) - Multiple Imputation with LightGBM in Python. <code>βUnlicensed</code>
- <b><a href="https://github.com/carefree0910/carefree-learn">carefree-learn</a></b> (π₯18 Β· β 410 Β· π) - 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> (π₯13 Β· β 550 Β· π) - DeltaPy - Tabular Data Augmentation (by @firmai). <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
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> (π₯44 Β· 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 (π¨βπ» 320 Β· π 9.2K Β· π₯ 2M Β· π¦ 6.2K Β· π 10K - 1% open Β· β±οΈ 30.10.2025):
git clone https://github.com/PaddlePaddle/PaddleOCR -
PyPi (π₯ 750K / month Β· π¦ 210 Β· β±οΈ 29.10.2025):
pip install paddleocr
-
GitHub (π¨βπ» 120 Β· π 2.2K Β· π₯ 15K Β· π¦ 1.4K Β· π 1.3K - 11% open Β· β±οΈ 25.10.2025):
git clone https://github.com/ocrmypdf/OCRmyPDF -
PyPi (π₯ 400K / month Β· π¦ 58 Β· β±οΈ 16.10.2025):
pip install ocrmypdf -
Conda (π₯ 110K Β· β±οΈ 22.04.2025):
conda install -c conda-forge ocrmypdf
-
GitHub (π¨βπ» 50 Β· π 730 Β· π 370 - 3% open Β· β±οΈ 17.02.2025):
git clone https://github.com/madmaze/pytesseract -
PyPi (π₯ 5.6M / month Β· π¦ 970 Β· β±οΈ 16.08.2024):
pip install pytesseract -
Conda (π₯ 690K Β· β±οΈ 22.04.2025):
conda install -c conda-forge pytesseract
-
GitHub (π¨βπ» 34 Β· π 260 Β· π₯ 1.2K Β· π¦ 1.3K Β· π 290 - 14% open Β· β±οΈ 10.10.2025):
git clone https://github.com/sirfz/tesserocr -
PyPi (π₯ 210K / month Β· π¦ 56 Β· β±οΈ 10.10.2025):
pip install tesserocr -
Conda (π₯ 290K Β· β±οΈ 22.04.2025):
conda install -c conda-forge tesserocr
-
GitHub (π¨βπ» 90 Β· π 770 Β· π¦ 240 Β· π 930 - 20% open Β· β±οΈ 27.11.2024):
git clone https://github.com/open-mmlab/mmocr -
PyPi (π₯ 6K / month Β· π¦ 4 Β· β±οΈ 05.05.2022):
pip install mmocr
-
GitHub (π¨βπ» 19 Β· π 340 Β· π₯ 2.1M Β· π¦ 720 Β· π 220 - 46% open Β· β±οΈ 22.09.2025):
git clone https://github.com/faustomorales/keras-ocr -
PyPi (π₯ 18K / month Β· π¦ 8 Β· β±οΈ 06.11.2023):
pip install keras-ocr -
Conda (π₯ 450 Β· β±οΈ 22.04.2025):
conda install -c anaconda keras-ocr
- <b><a href="https://github.com/JaidedAI/EasyOCR">EasyOCR</a></b> (π₯34 Β· β 28K Β· π) - 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> (π₯22 Β· β 1.2K) - Line based ATR Engine based on OCRopy. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/WZBSocialScienceCenter/pdftabextract">pdftabextract</a></b> (π₯21 Β· β 2.2K Β· π) - 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> (π₯21 Β· β 1.1K Β· π) - 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> (π₯20 Β· β 1.3K Β· π) - 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> (π₯10 Β· β 690 Β· π) - 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>
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.
πΒ <b><a href="https://github.com/ml-tooling/best-of-python#data-containers--dataframes">best-of-python - Data Containers</a></b> ( β 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.
πΒ <b><a href="https://github.com/ml-tooling/best-of-python#data-loading--extraction">best-of-python - Data Extraction</a></b> ( β 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.
πΒ <b><a href="https://github.com/ml-tooling/best-of-web-python#web-scraping--crawling">best-of-web-python - Web Scraping</a></b> ( β 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.
πΒ <b><a href="https://github.com/ml-tooling/best-of-python#data-pipelines--streaming">best-of-python - Data Pipelines</a></b> ( β 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> (π₯10 Β· β 10) - Multidimensional cluster generation in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
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> (π₯48 Β· 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 (π¨βπ» 1.4K Β· π 6.8K Β· π₯ 270 Β· π¦ 27K Β· π 22K - 14% open Β· β±οΈ 30.10.2025):
git clone https://github.com/ray-project/ray -
PyPi (π₯ 30M / month Β· π¦ 1.1K Β· β±οΈ 29.10.2025):
pip install ray -
Conda (π₯ 920K Β· β±οΈ 22.10.2025):
conda install -c conda-forge ray-tune
-
GitHub (π¨βπ» 630 Β· π 1.8K Β· π¦ 77K Β· π 5.6K - 21% open Β· β±οΈ 29.10.2025):
git clone https://github.com/dask/dask -
PyPi (π₯ 20M / month Β· π¦ 3.2K Β· β±οΈ 14.10.2025):
pip install dask -
Conda (π₯ 14M Β· β±οΈ 14.10.2025):
conda install -c conda-forge dask
-
GitHub (π¨βπ» 420 Β· π 4.6K Β· π¦ 15K Β· π 3.2K - 34% open Β· β±οΈ 29.10.2025):
git clone https://github.com/microsoft/DeepSpeed -
PyPi (π₯ 990K / month Β· π¦ 350 Β· β±οΈ 23.10.2025):
pip install deepspeed -
Docker Hub (π₯ 24K Β· β 4 Β· β±οΈ 02.09.2022):
docker pull deepspeed/deepspeed
-
GitHub (π¨βπ» 340 Β· π 740 Β· π¦ 42K Β· π 3.9K - 37% open Β· β±οΈ 28.10.2025):
git clone https://github.com/dask/distributed -
PyPi (π₯ 5.4M / month Β· π¦ 1K Β· β±οΈ 14.10.2025):
pip install distributed -
Conda (π₯ 20M Β· β±οΈ 14.10.2025):
conda install -c conda-forge distributed
-
GitHub (π¨βπ» 180 Β· π 2.3K Β· π¦ 1.4K Β· π 2.3K - 17% open Β· β±οΈ 28.10.2025):
git clone https://github.com/horovod/horovod -
PyPi (π₯ 78K / month Β· π¦ 34 Β· β±οΈ 12.06.2023):
pip install horovod
-
GitHub (π¨βπ» 280 Β· π 460 Β· π₯ 6.9K Β· π¦ 45K Β· π 990 - 8% open Β· β±οΈ 27.10.2025):
git clone https://github.com/Lightning-AI/metrics -
PyPi (π₯ 4.6K / month Β· π¦ 4 Β· β±οΈ 26.02.2025):
pip install metrics -
Conda (π₯ 2.2M Β· β±οΈ 03.09.2025):
conda install -c conda-forge torchmetrics
-
GitHub (π¨βπ» 280 Β· π 2K Β· π¦ 99 Β· π 9.6K - 30% open Β· β±οΈ 21.10.2025):
git clone https://github.com/h2oai/h2o-3 -
PyPi (π₯ 180K / month Β· π¦ 68 Β· β±οΈ 08.10.2025):
pip install h2o
-
GitHub (π¨βπ» 200 Β· π 4.5K Β· π¦ 530 Β· π 1.8K - 26% open Β· β±οΈ 26.09.2025):
git clone https://github.com/hpcaitech/colossalai
-
GitHub (π¨βπ» 28 Β· π 130 Β· π₯ 39K Β· π¦ 12K Β· π 230 - 2% open Β· β±οΈ 29.10.2025):
git clone https://github.com/mpi4py/mpi4py -
PyPi (π₯ 980K / month Β· π¦ 1K Β· β±οΈ 10.10.2025):
pip install mpi4py -
Conda (π₯ 4.5M Β· β±οΈ 14.10.2025):
conda install -c conda-forge mpi4py
-
GitHub (π¨βπ» 77 Β· π 290 Β· π¦ 9K Β· π 390 - 26% open Β· β±οΈ 26.04.2025):
git clone https://github.com/facebookresearch/fairscale -
PyPi (π₯ 530K / month Β· π¦ 150 Β· β±οΈ 11.12.2022):
pip install fairscale -
Conda (π₯ 530K Β· β±οΈ 22.04.2025):
conda install -c conda-forge fairscale
-
GitHub (π¨βπ» 26 Β· π 140 Β· π¦ 4.7K Β· π 130 - 38% open Β· β±οΈ 21.05.2025):
git clone https://github.com/facebookincubator/submitit -
PyPi (π₯ 840K / month Β· π¦ 74 Β· β±οΈ 21.05.2025):
pip install submitit -
Conda (π₯ 65K Β· β±οΈ 22.04.2025):
conda install -c conda-forge submitit
-
GitHub (π¨βπ» 120 Β· π 1.4K Β· π₯ 710 Β· π 3K - 40% open Β· β±οΈ 14.10.2025):
git clone https://github.com/intel-analytics/BigDL -
PyPi (π₯ 15K / month Β· π¦ 2 Β· β±οΈ 24.03.2024):
pip install bigdl -
Maven (π¦ 5 Β· β±οΈ 20.04.2021):
<dependency> <groupId>com.intel.analytics.bigdl</groupId> <artifactId>bigdl-SPARK_2.4</artifactId> <version>[VERSION]</version> </dependency>
-
GitHub (π¨βπ» 130 Β· π 850 Β· π 820 - 49% open Β· β±οΈ 29.10.2025):
git clone https://github.com/microsoft/SynapseML -
PyPi (π₯ 1.6M / month Β· π¦ 7 Β· β±οΈ 03.10.2025):
pip install synapseml
-
GitHub (π¨βπ» 52 Β· π 280 Β· π₯ 580 Β· π¦ 390 Β· π 330 - 54% open Β· β±οΈ 15.09.2025):
git clone https://github.com/uber/petastorm -
PyPi (π₯ 270K / month Β· π¦ 15 Β· β±οΈ 11.08.2025):
pip install petastorm
-
GitHub (π¨βπ» 82 Β· π 260 Β· π¦ 1.3K Β· π 550 - 51% open Β· β±οΈ 27.09.2025):
git clone https://github.com/dask/dask-ml -
PyPi (π₯ 120K / month Β· π¦ 100 Β· β±οΈ 08.02.2025):
pip install dask-ml -
Conda (π₯ 1.1M Β· β±οΈ 22.04.2025):
conda install -c conda-forge dask-ml
-
GitHub (π¨βπ» 34 Β· π 190 Β· π¦ 130 Β· π 190 - 43% open Β· β±οΈ 12.10.2025):
git clone https://github.com/learning-at-home/hivemind -
PyPi (π₯ 43K / month Β· π¦ 12 Β· β±οΈ 20.04.2025):
pip install hivemind
-
GitHub (π¨βπ» 130 Β· π 850 Β· π 820 - 49% open Β· β±οΈ 29.10.2025):
git clone https://github.com/microsoft/SynapseML -
PyPi (β±οΈ 18.03.2020):
pip install mmlspark
-
GitHub (π¨βπ» 98 Β· π 1.3K Β· π¦ 6 Β· π 140 - 35% open Β· β±οΈ 26.03.2025):
git clone https://github.com/apache/singa -
Conda (π₯ 1.2K Β· β±οΈ 25.03.2025):
conda install -c nusdbsystem singa -
Docker Hub (π₯ 9.9K Β· β 3 Β· β±οΈ 31.05.2022):
docker pull apache/singa
-
GitHub (π¨βπ» 110 Β· π 730 Β· π 1.3K - 32% open Β· β±οΈ 09.10.2025):
git clone https://github.com/intel-analytics/analytics-zoo -
PyPi (π₯ 600 / month Β· π¦ 1 Β· β±οΈ 22.08.2022):
pip install analytics-zoo
- <b><a href="https://github.com/DEAP/deap">DEAP</a></b> (π₯34 Β· β 6.2K) - Distributed Evolutionary Algorithms in Python. <code><a href="http://bit.ly/37RvQcA">βοΈLGPL-3.0</a></code>
- <b><a href="https://github.com/ipython/ipyparallel">ipyparallel</a></b> (π₯29 Β· β 2.6K) - IPython Parallel: Interactive Parallel Computing in.. <code>βUnlicensed</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> (π₯25 Β· β 3.9K Β· π) - 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> (π₯24 Β· β 1.6K Β· π) - 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> (π₯23 Β· β 1.6K Β· π) - 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> (π₯21 Β· β 3.7K Β· π) - 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> (π₯21 Β· β 280 Β· π) - 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> (π₯19 Β· β 750 Β· π) - [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> (π₯19 Β· β 290 Β· π) - 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> (π₯18 Β· β 6.4K Β· π) - 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> (π₯18 Β· β 330 Β· π) - 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> (π₯17 Β· β 1K Β· π) - 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> (π₯17 Β· β 290 Β· π) - 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> (π₯16 Β· β 790 Β· π) - 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> (π₯13 Β· β 49 Β· π) - 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> (π₯12 Β· β 130 Β· π) - 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> (π₯11 Β· β 370 Β· π) - 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>
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> (π₯44 Β· β 13K) - A hyperparameter optimization framework. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>-
GitHub (π¨βπ» 320 Β· π 1.2K Β· π¦ 30K Β· π 1.8K - 3% open Β· β±οΈ 30.10.2025):
git clone https://github.com/optuna/optuna -
PyPi (π₯ 7.6M / month Β· π¦ 1.5K Β· β±οΈ 18.08.2025):
pip install optuna -
Conda (π₯ 3.4M Β· β±οΈ 19.08.2025):
conda install -c conda-forge optuna
-
GitHub (π¨βπ» 200 Β· π 350 Β· π¦ 1.2K Β· π 930 - 12% open Β· β±οΈ 30.10.2025):
git clone https://github.com/facebook/Ax -
PyPi (π₯ 240K / month Β· π¦ 71 Β· β±οΈ 09.09.2025):
pip install ax-platform -
Conda (π₯ 49K Β· β±οΈ 10.09.2025):
conda install -c conda-forge ax-platform
-
GitHub (π¨βπ» 140 Β· π 1.1K Β· π¦ 1.2K Β· π 1.8K - 24% open Β· β±οΈ 29.10.2025):
git clone https://github.com/autogluon/autogluon -
PyPi (π₯ 260K / month Β· π¦ 38 Β· β±οΈ 23.10.2025):
pip install autogluon -
Conda (π₯ 45K Β· β±οΈ 30.07.2025):
conda install -c conda-forge autogluon -
Docker Hub (π₯ 20K Β· β 19 Β· β±οΈ 16.06.2025):
docker pull autogluon/autogluon
-
GitHub (π¨βπ» 150 Β· π 450 Β· π¦ 1.8K Β· π 600 - 10% open Β· β±οΈ 29.10.2025):
git clone https://github.com/pytorch/botorch -
PyPi (π₯ 480K / month Β· π¦ 140 Β· β±οΈ 23.10.2025):
pip install botorch -
Conda (π₯ 180K Β· β±οΈ 24.10.2025):
conda install -c conda-forge botorch
-
GitHub (π¨βπ» 52 Β· π 1.6K Β· π₯ 180 Β· π¦ 4.1K Β· π 390 - 1% open Β· β±οΈ 09.09.2025):
git clone https://github.com/fmfn/BayesianOptimization -
PyPi (π₯ 510K / month Β· π¦ 190 Β· β±οΈ 24.07.2025):
pip install bayesian-optimization
-
GitHub (π¨βπ» 100 Β· π 1.1K Β· π¦ 22K Β· π 800 - 17% open Β· β±οΈ 27.12.2024):
git clone https://github.com/hyperopt/hyperopt -
PyPi (π₯ 2.7M / month Β· π¦ 450 Β· β±οΈ 17.11.2021):
pip install hyperopt -
Conda (π₯ 860K Β· β±οΈ 22.04.2025):
conda install -c conda-forge hyperopt
-
GitHub (π¨βπ» 150 Β· π 1.4K Β· π₯ 21K Β· π¦ 890 Β· π 910 - 16% open Β· β±οΈ 16.12.2024):
git clone https://github.com/keras-team/autokeras -
PyPi (π₯ 15K / month Β· π¦ 13 Β· β±οΈ 20.03.2024):
pip install autokeras
-
GitHub (π¨βπ» 75 Β· π 900 Β· π¦ 2.1K Β· π 1K - 15% open Β· β±οΈ 13.11.2024):
git clone https://github.com/alteryx/featuretools -
PyPi (π₯ 100K / month Β· π¦ 74 Β· β±οΈ 14.05.2024):
pip install featuretools -
Conda (π₯ 270K Β· β±οΈ 22.04.2025):
conda install -c conda-forge featuretools
-
GitHub (π¨βπ» 58 Β· π 360 Β· π¦ 1.2K Β· π 310 - 40% open Β· β±οΈ 23.04.2025):
git clone https://github.com/facebookresearch/nevergrad -
PyPi (π₯ 150K / month Β· π¦ 72 Β· β±οΈ 23.04.2025):
pip install nevergrad -
Conda (π₯ 67K Β· β±οΈ 22.04.2025):
conda install -c conda-forge nevergrad
-
GitHub (π¨βπ» 19 Β· π 360 Β· π¦ 1.4K Β· π 160 - 64% open Β· β±οΈ 17.10.2025):
git clone https://github.com/shankarpandala/lazypredict -
PyPi (π₯ 31K / month Β· π¦ 8 Β· β±οΈ 05.04.2025):
pip install lazypredict -
Conda (π₯ 6.6K Β· β±οΈ 22.04.2025):
conda install -c conda-forge lazypredict
-
GitHub (π¨βπ» 30 Β· π 420 Β· π¦ 170 Β· π 680 - 21% open Β· β±οΈ 07.07.2025):
git clone https://github.com/mljar/mljar-supervised -
PyPi (π₯ 8.7K / month Β· π¦ 6 Β· β±οΈ 07.07.2025):
pip install mljar-supervised -
Conda (π₯ 52K Β· β±οΈ 08.07.2025):
conda install -c conda-forge mljar-supervised
-
GitHub (π¨βπ» 15 Β· π 51 Β· π₯ 340 Β· π¦ 40 Β· π 120 - 28% open Β· β±οΈ 25.10.2025):
git clone https://github.com/SimonBlanke/Hyperactive -
PyPi (π₯ 4K / month Β· π¦ 13 Β· β±οΈ 20.09.2025):
pip install hyperactive
-
GitHub (π¨βπ» 40 Β· π 89 Β· π¦ 65 Β· π 570 - 11% open Β· β±οΈ 14.10.2025):
git clone https://github.com/nccr-itmo/FEDOT -
PyPi (π₯ 1.8K / month Β· π¦ 7 Β· β±οΈ 10.03.2025):
pip install fedot
-
GitHub (π¨βπ» 5 Β· π 250 Β· π¦ 10 Β· π 45 - 35% open Β· β±οΈ 24.08.2025):
git clone https://github.com/ScottfreeLLC/AlphaPy -
PyPi (π₯ 320 / month Β· β±οΈ 29.08.2020):
pip install alphapy
-
GitHub (π¨βπ» 9 Β· π 100 Β· π¦ 28 Β· β±οΈ 30.01.2025):
git clone https://github.com/AutoViML/Auto_ViML -
PyPi (π₯ 2.6K / month Β· π¦ 3 Β· β±οΈ 30.01.2025):
pip install autoviml
-
GitHub (π¨βπ» 18 Β· π 98 Β· π 110 - 0% open Β· β±οΈ 19.02.2025):
git clone https://github.com/AutoViML/featurewiz -
PyPi (π₯ 4.6K / month Β· π¦ 4 Β· β±οΈ 19.02.2025):
pip install featurewiz
- <b><a href="https://github.com/EpistasisLab/tpot">TPOT</a></b> (π₯32 Β· β 10K) - A Python Automated Machine Learning tool that optimizes machine.. <code><a href="http://bit.ly/37RvQcA">βοΈLGPL-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> (π₯32 Β· β 2.9K Β· π) - 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> (π₯32 Β· β 2.8K Β· π) - 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> (π₯31 Β· β 14K Β· π) - 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> (π₯31 Β· β 8K Β· π) - 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> (π₯27 Β· β 2.2K Β· π) - 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> (π₯27 Β· β 1.2K Β· π€) - SMAC3: A Versatile Bayesian Optimization Package for.. <code><a href="https://tldrlegal.com/search?q=BSD-1-Clause">βοΈBSD-1-Clause</a></code>
- <b><a href="https://github.com/SheffieldML/GPyOpt">GPyOpt</a></b> (π₯26 Β· β 950 Β· π) - 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> (π₯24 Β· β 3.5K Β· π) - 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> (π₯24 Β· β 1.7K Β· π) - [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> (π₯24 Β· β 1.6K Β· π) - 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> (π₯24 Β· β 490) - Lightwood is Legos for Machine Learning. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-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> (π₯24 Β· β 300 Β· π) - 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> (π₯22 Β· β 620 Β· π) - 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> (π₯21 Β· β 1.5K Β· π) - MLBox is a powerful Automated Machine Learning python library. <code><a href="https://tldrlegal.com/search?q=BSD-1-Clause">βοΈBSD-1-Clause</a></code>
- <b><a href="https://github.com/williamFalcon/test-tube">Test Tube</a></b> (π₯21 Β· β 740 Β· π) - 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> (π₯21 Β· β 610 Β· π) - 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> (π₯21 Β· β 420 Β· π) - 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> (π₯20 Β· β 770 Β· π) - 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> (π₯20 Β· β 630 Β· π) - 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> (π₯19 Β· β 3.1K Β· π) - 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> (π₯19 Β· β 890 Β· π) - 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> (π₯19 Β· β 530 Β· π) - 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> (π₯19 Β· β 340 Β· π) - Hyperparameter optimization that enables researchers to.. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/cerlymarco/shap-hypetune">shap-hypetune</a></b> (π₯18 Β· β 580 Β· π) - 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> (π₯17 Β· β 1.6K Β· π) - 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> (π₯17 Β· β 1.3K Β· π) - 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> (π₯16 Β· β 1.9K Β· π) - 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> (π₯16 Β· β 710 Β· π) - 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> (π₯15 Β· β 200 Β· π) - 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> (π₯13 Β· β 2.7K Β· π) - 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> (π₯12 Β· β 200 Β· π) - An automatic ML model optimization tool. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/genixpro/hypermax">Hypermax</a></b> (π₯12 Β· β 110 Β· π) - 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> (π₯11 Β· β 3.3K Β· π) - 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> (π₯11 Β· β 950 Β· π) - 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> (π₯9 Β· β 140 Β· π) - A toolset for black-box hyperparameter optimisation. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
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> (π₯30 Β· β 13K) - FinRL: Financial Reinforcement Learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>-
GitHub (π¨βπ» 130 Β· π 2.9K Β· π¦ 110 Β· π 760 - 35% open Β· β±οΈ 03.10.2025):
git clone https://github.com/AI4Finance-Foundation/FinRL -
PyPi (π₯ 2.8K / month Β· β±οΈ 08.01.2022):
pip install finrl
-
GitHub (π¨βπ» 57 Β· π 400 Β· π₯ 12K Β· π¦ 340 Β· π 470 - 6% open Β· β±οΈ 26.10.2025):
git clone https://github.com/mwydmuch/ViZDoom -
PyPi (π₯ 6.9K / month Β· π¦ 20 Β· β±οΈ 22.10.2025):
pip install vizdoom
-
GitHub (π¨βπ» 15 Β· π 1.4K Β· π¦ 21 Β· π 200 - 55% open Β· β±οΈ 04.11.2024):
git clone https://github.com/google/dopamine -
PyPi (π₯ 68K / month Β· π¦ 10 Β· β±οΈ 31.10.2024):
pip install dopamine-rl
-
GitHub (π¨βπ» 90 Β· π 500 Β· π¦ 250 Β· π 270 - 24% open Β· β±οΈ 26.09.2025):
git clone https://github.com/deepmind/acme -
PyPi (π₯ 6.4K / month Β· π¦ 3 Β· β±οΈ 10.02.2022):
pip install dm-acme -
Conda (π₯ 14K Β· β±οΈ 22.04.2025):
conda install -c conda-forge dm-acme
-
GitHub (π¨βπ» 150 Β· π 740 Β· π 680 - 30% open Β· β±οΈ 16.06.2025):
git clone https://github.com/tensorflow/agents -
PyPi (π₯ 45K / month Β· π¦ 14 Β· β±οΈ 14.12.2023):
pip install tf-agents
-
GitHub (π¨βπ» 23 Β· π 95 Β· π¦ 370 Β· π 28 - 32% open Β· β±οΈ 26.09.2025):
git clone https://github.com/deepmind/rlax -
PyPi (π₯ 48K / month Β· π¦ 22 Β· β±οΈ 01.09.2025):
pip install rlax
-
GitHub (π¨βπ» 46 Β· π 820 Β· π¦ 140 Β· π 540 - 23% open Β· β±οΈ 13.09.2025):
git clone https://github.com/PaddlePaddle/PARL -
PyPi (π₯ 770 / month Β· π¦ 1 Β· β±οΈ 13.05.2022):
pip install parl
-
GitHub (π¨βπ» 170 Β· π 520 Β· π 160 - 53% open Β· β±οΈ 17.10.2025):
git clone https://github.com/facebookresearch/ReAgent -
PyPi (π₯ 50 / month Β· β±οΈ 27.05.2020):
pip install reagent
- <b><a href="https://github.com/openai/gym">OpenAI Gym</a></b> (π₯40 Β· β 37K Β· π) - 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> (π₯29 Β· β 17K Β· π) - 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> (π₯28 Β· β 5.6K Β· π) - 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> (π₯27 Β· β 7.4K Β· π) - 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> (π₯27 Β· β 3.3K Β· π) - 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> (π₯26 Β· β 2K Β· π) - 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> (π₯25 Β· β 1.2K Β· π) - 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> (π₯24 Β· β 4.3K Β· π) - 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> (π₯23 Β· β 1.2K Β· π) - 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> (π₯22 Β· β 3.1K Β· π) - 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> (π₯20 Β· β 2.3K Β· π) - 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> (π₯19 Β· β 6.9K Β· π) - 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> (π₯17 Β· β 7.3K Β· π) - A customisable 3D platform for agent-based AI research. <code>βUnlicensed</code>
- <b><a href="https://github.com/enlite-ai/maze">Maze</a></b> (π₯12 Β· β 280 Β· π) - Maze Applied Reinforcement Learning Framework. <code><a href="https://tldrlegal.com/search?q=Custom">βοΈCustom</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> (π₯11 Β· β 850 Β· π) - [NeurIPS21 Outstanding Paper] Library for reliable evaluation on.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
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> (π₯33 Β· β 21K) - Best Practices on Recommendation Systems. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>-
GitHub (π¨βπ» 140 Β· π 3.2K Β· π₯ 790 Β· π¦ 180 Β· π 890 - 18% open Β· β±οΈ 13.10.2025):
git clone https://github.com/microsoft/recommenders -
PyPi (π₯ 15K / month Β· π¦ 4 Β· β±οΈ 24.12.2024):
pip install recommenders
-
GitHub (π¨βπ» 400 Β· π 560 Β· π¦ 240 Β· π 320 - 49% open Β· β±οΈ 30.10.2025):
git clone https://github.com/pytorch/torchrec -
PyPi (π₯ 160 / month Β· β±οΈ 12.05.2022):
pip install torchrec-nightly-cpu
-
GitHub (π¨βπ» 24 Β· π 160 Β· π¦ 300 Β· π 170 - 17% open Β· β±οΈ 04.10.2025):
git clone https://github.com/PreferredAI/cornac -
PyPi (π₯ 44K / month Β· π¦ 18 Β· β±οΈ 04.10.2025):
pip install cornac -
Conda (π₯ 920K Β· β±οΈ 05.10.2025):
conda install -c conda-forge cornac
-
GitHub (π¨βπ» 41 Β· π 72 Β· π¦ 140 Β· π 290 - 33% open Β· β±οΈ 29.10.2025):
git clone https://github.com/lenskit/lkpy -
PyPi (π₯ 6.6K / month Β· π¦ 13 Β· β±οΈ 22.10.2025):
pip install lenskit -
Conda (π₯ 52K Β· β±οΈ 23.10.2025):
conda install -c conda-forge lenskit
-
GitHub (π¨βπ» 79 Β· π 690 Β· π 1.1K - 32% open Β· β±οΈ 24.02.2025):
git clone https://github.com/RUCAIBox/RecBole -
PyPi (π₯ 98K / month Β· π¦ 2 Β· β±οΈ 24.02.2025):
pip install recbole -
Conda (π₯ 9.3K Β· β±οΈ 25.03.2025):
conda install -c aibox recbole
-
GitHub (π¨βπ» 45 Β· π 290 Β· π 450 - 59% open Β· β±οΈ 27.09.2025):
git clone https://github.com/tensorflow/recommenders -
PyPi (π₯ 220K / month Β· π¦ 2 Β· β±οΈ 03.02.2023):
pip install tensorflow-recommenders
- <b><a href="https://github.com/benfred/implicit">implicit</a></b> (π₯30 Β· β 3.7K Β· π) - 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> (π₯28 Β· β 5K Β· π) - 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> (π₯27 Β· β 6.7K Β· π) - 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> (π₯26 Β· β 2.8K Β· π) - 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> (π₯22 Β· β 1.1K Β· π) - 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> (π₯21 Β· β 1.3K Β· π) - 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> (π₯18 Β· β 3K Β· π) - 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> (π₯18 Β· β 580 Β· π) - 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> (π₯18 Β· β 500 Β· π) - 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> (π₯16 Β· β 420 Β· π) - 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> (π₯10 Β· β 100 Β· π) - 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>
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> (π₯32 Β· 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 (π¨βπ» 87 Β· π 370 Β· π₯ 150 Β· π¦ 1.2K Β· π 340 - 19% open Β· β±οΈ 27.10.2025):
git clone https://github.com/pytorch/opacus -
PyPi (π₯ 92K / month Β· π¦ 49 Β· β±οΈ 27.05.2025):
pip install opacus -
Conda (π₯ 28K Β· β±οΈ 09.07.2025):
conda install -c conda-forge opacus
-
GitHub (π¨βπ» 520 Β· π 2K Β· π₯ 2.1K Β· π¦ 1 Β· π 3.4K - 1% open Β· β±οΈ 13.04.2025):
git clone https://github.com/OpenMined/PySyft -
PyPi (π₯ 32K / month Β· π¦ 5 Β· β±οΈ 13.04.2025):
pip install syft
-
GitHub (π¨βπ» 60 Β· π 460 Β· π₯ 190 Β· π 210 - 55% open Β· β±οΈ 13.06.2025):
git clone https://github.com/tensorflow/privacy -
PyPi (π₯ 18K / month Β· π¦ 21 Β· β±οΈ 14.02.2024):
pip install tensorflow-privacy
-
GitHub (π¨βπ» 100 Β· π 1.6K Β· π¦ 1 Β· π 2.1K - 2% open Β· β±οΈ 19.11.2024):
git clone https://github.com/FederatedAI/FATE -
PyPi (β±οΈ 06.05.2020):
pip install ETAF
-
GitHub (π¨βπ» 40 Β· π 290 Β· π 280 - 28% open Β· β±οΈ 23.11.2024):
git clone https://github.com/facebookresearch/CrypTen -
PyPi (π₯ 600 / month Β· π¦ 1 Β· β±οΈ 08.12.2022):
pip install crypten
- <b><a href="https://github.com/tf-encrypted/tf-encrypted">TFEncrypted</a></b> (π₯24 Β· β 1.2K Β· π) - 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> (π₯19 Β· β 280) - PipelineDP is a Python framework for applying differentially.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
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> (π₯47 Β· 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 (π¨βπ» 910 Β· π 4.9K Β· π¦ 66K Β· π 5.2K - 39% open Β· β±οΈ 30.10.2025):
git clone https://github.com/mlflow/mlflow -
PyPi (π₯ 26M / month Β· π¦ 1.3K Β· β±οΈ 22.10.2025):
pip install mlflow -
Conda (π₯ 3.7M Β· β±οΈ 24.10.2025):
conda install -c conda-forge mlflow
-
GitHub (π¨βπ» 220 Β· π 790 Β· π₯ 1.2K Β· π¦ 84K Β· π 3.7K - 18% open Β· β±οΈ 30.10.2025):
git clone https://github.com/wandb/client -
PyPi (π₯ 20M / month Β· π¦ 2.3K Β· β±οΈ 28.10.2025):
pip install wandb -
Conda (π₯ 1.2M Β· β±οΈ 30.10.2025):
conda install -c conda-forge wandb
-
GitHub (π¨βπ» 320 Β· π 1.2K Β· π¦ 24K Β· π 4.9K - 4% open Β· β±οΈ 28.10.2025):
git clone https://github.com/iterative/dvc -
PyPi (π₯ 1.5M / month Β· π¦ 140 Β· β±οΈ 02.09.2025):
pip install dvc -
Conda (π₯ 3.1M Β· β±οΈ 02.09.2025):
conda install -c conda-forge dvc
-
GitHub (π¨βπ» 330 Β· π 1.7K Β· π¦ 330K Β· π 2K - 36% open Β· β±οΈ 12.08.2025):
git clone https://github.com/tensorflow/tensorboard -
PyPi (π₯ 31M / month Β· π¦ 2.8K Β· β±οΈ 17.07.2025):
pip install tensorboard -
Conda (π₯ 6M Β· β±οΈ 18.07.2025):
conda install -c conda-forge tensorboard
-
GitHub (π¨βπ» 500 Β· π 1.2K Β· π¦ 6.2K Β· π 1.6K - 21% open Β· β±οΈ 29.10.2025):
git clone https://github.com/aws/sagemaker-python-sdk -
PyPi (π₯ 27M / month Β· π¦ 210 Β· β±οΈ 29.10.2025):
pip install sagemaker -
Conda (π₯ 1.8M Β· β±οΈ 30.10.2025):
conda install -c conda-forge sagemaker-python-sdk
-
GitHub (π¨βπ» 120 Β· π 930 Β· π¦ 950 Β· π 840 - 43% open Β· β±οΈ 29.10.2025):
git clone https://github.com/Netflix/metaflow -
PyPi (π₯ 740K / month Β· π¦ 53 Β· β±οΈ 29.10.2025):
pip install metaflow -
Conda (π₯ 340K Β· β±οΈ 29.10.2025):
conda install -c conda-forge metaflow
-
GitHub (π¨βπ» 85 Β· π 860 Β· π₯ 500 Β· π¦ 60K Β· π 470 - 18% open Β· β±οΈ 13.06.2025):
git clone https://github.com/lanpa/tensorboardX -
PyPi (π₯ 4.5M / month Β· π¦ 740 Β· β±οΈ 10.06.2025):
pip install tensorboardX -
Conda (π₯ 1.3M Β· β±οΈ 22.04.2025):
conda install -c conda-forge tensorboardx
-
GitHub (π¨βπ» 140 Β· π 1.8K Β· π₯ 730 Β· π¦ 7.9K Β· π 2.3K - 16% open Β· β±οΈ 06.03.2025):
git clone https://github.com/pycaret/pycaret -
PyPi (π₯ 310K / month Β· π¦ 31 Β· β±οΈ 28.04.2024):
pip install pycaret -
Conda (π₯ 78K Β· β±οΈ 22.04.2025):
conda install -c conda-forge pycaret
-
GitHub (π¨βπ» 100 Β· π 710 Β· π₯ 3.5K Β· π¦ 1.9K Β· π 1.2K - 45% open Β· β±οΈ 27.10.2025):
git clone https://github.com/allegroai/clearml -
PyPi (π₯ 500K / month Β· π¦ 78 Β· β±οΈ 22.10.2025):
pip install clearml -
Docker Hub (π₯ 31K Β· β±οΈ 05.10.2020):
docker pull allegroai/trains
-
GitHub (π¨βπ» 380 Β· π 610 Β· π¦ 2.5K Β· π 2.1K - 58% open Β· β±οΈ 29.10.2025):
git clone https://github.com/snakemake/snakemake -
PyPi (π₯ 130K / month Β· π¦ 320 Β· β±οΈ 22.10.2025):
pip install snakemake -
Conda (π₯ 1.5M Β· β±οΈ 28.10.2025):
conda install -c bioconda snakemake
-
GitHub (π¨βπ» 49 Β· π 1.2K Β· π¦ 21 Β· π 530 - 27% open Β· β±οΈ 28.10.2025):
git clone https://github.com/Kaggle/kaggle-api -
PyPi (π₯ 610K / month Β· π¦ 240 Β· β±οΈ 08.05.2025):
pip install kaggle -
Conda (π₯ 250K Β· β±οΈ 11.08.2025):
conda install -c conda-forge kaggle
-
GitHub (π¨βπ» 82 Β· π 360 Β· π¦ 1.1K Β· π 1.1K - 37% open Β· β±οΈ 26.06.2025):
git clone https://github.com/aimhubio/aim -
PyPi (π₯ 120K / month Β· π¦ 56 Β· β±οΈ 11.06.2025):
pip install aim -
Conda (π₯ 140K Β· β±οΈ 22.04.2025):
conda install -c conda-forge aim
-
GitHub (π¨βπ» 65 Β· π 2.5K Β· π₯ 680 Β· π 1.5K - 26% open Β· β±οΈ 14.03.2025):
git clone https://github.com/Azure/MachineLearningNotebooks -
PyPi (π₯ 2.2M / month Β· π¦ 31 Β· β±οΈ 11.04.2025):
pip install azureml-sdk
-
GitHub (π¨βπ» 36 Β· π 630 Β· π₯ 540 Β· π¦ 3.6K Β· π 510 - 30% open Β· β±οΈ 22.01.2025):
git clone https://github.com/PaddlePaddle/VisualDL -
PyPi (π₯ 170K / month Β· π¦ 82 Β· β±οΈ 30.10.2024):
pip install visualdl
-
GitHub (π¨βπ» 110 Β· π 390 Β· π¦ 3.6K Β· π 560 - 18% open Β· β±οΈ 22.10.2025):
git clone https://github.com/IDSIA/sacred -
PyPi (π₯ 48K / month Β· π¦ 60 Β· β±οΈ 26.11.2024):
pip install sacred -
Conda (π₯ 9.9K Β· β±οΈ 22.04.2025):
conda install -c conda-forge sacred
-
GitHub (π¨βπ» 57 Β· π 66 Β· π¦ 920 Β· π 260 - 12% open Β· β±οΈ 09.06.2025):
git clone https://github.com/neptune-ai/neptune-client -
PyPi (π₯ 480K / month Β· π¦ 77 Β· β±οΈ 15.04.2025):
pip install neptune-client -
Conda (π₯ 390K Β· β±οΈ 22.04.2025):
conda install -c conda-forge neptune-client
-
GitHub (π¨βπ» 150 Β· π 290 Β· π 150 - 56% open Β· β±οΈ 09.10.2025):
git clone https://github.com/pytorch/tnt -
PyPi (π₯ 9.4K / month Β· π¦ 24 Β· β±οΈ 29.07.2018):
pip install torchnet
-
GitHub (π¨βπ» 17 Β· π 140 Β· π¦ 1.9K Β· π 79 - 7% open Β· β±οΈ 03.01.2025):
git clone https://github.com/stared/livelossplot -
PyPi (π₯ 19K / month Β· π¦ 16 Β· β±οΈ 03.01.2025):
pip install livelossplot
-
GitHub (π¨βπ» 23 Β· π 170 Β· π₯ 3K Β· π¦ 720 Β· π 130 - 41% open Β· β±οΈ 03.04.2025):
git clone https://github.com/google/ml-metadata -
PyPi (π₯ 50K / month Β· π¦ 32 Β· β±οΈ 07.04.2025):
pip install ml-metadata
-
GitHub (π¨βπ» 9 Β· π 140 Β· π¦ 240 Β· π 50 - 12% open Β· β±οΈ 10.04.2025):
git clone https://github.com/labmlai/labml -
PyPi (π₯ 4.6K / month Β· π¦ 14 Β· β±οΈ 15.09.2024):
pip install labml
-
GitHub (π¨βπ» 31 Β· π 98 Β· π₯ 69 Β· π¦ 94 Β· π 130 - 27% open Β· β±οΈ 06.12.2024):
git clone https://github.com/MrPowers/quinn -
PyPi (π₯ 750K / month Β· π¦ 7 Β· β±οΈ 13.02.2024):
pip install quinn
-
GitHub (π¨βπ» 48 Β· π 63 Β· π¦ 85 Β· π 100 - 31% open Β· β±οΈ 18.06.2025):
git clone https://github.com/m3dev/gokart -
PyPi (π₯ 6.7K / month Β· π¦ 8 Β· β±οΈ 18.06.2025):
pip install gokart
-
GitHub (π¨βπ» 30 Β· π 90 Β· π₯ 32 Β· π¦ 110 Β· π 440 - 50% open Β· β±οΈ 29.04.2025):
git clone https://github.com/guildai/guildai -
PyPi (π₯ 1.7K / month Β· β±οΈ 11.05.2022):
pip install guildai
-
GitHub (π¨βπ» 15 Β· π 360 Β· π¦ 160 Β· π 70 - 75% open Β· β±οΈ 27.09.2025):
git clone https://github.com/microsoft/tensorwatch -
PyPi (π₯ 1.4K / month Β· π¦ 7 Β· β±οΈ 04.03.2020):
pip install tensorwatch
-
GitHub (π¨βπ» 18 Β· π 71 Β· π 190 - 65% open Β· β±οΈ 03.12.2024):
git clone https://github.com/replicate/keepsake -
PyPi (π₯ 880 / month Β· π¦ 1 Β· β±οΈ 25.01.2021):
pip install keepsake
-
GitHub (π¨βπ» 6 Β· π 30 Β· π¦ 7 Β· π 180 - 17% open Β· β±οΈ 23.06.2025):
git clone https://github.com/datmo/datmo -
PyPi (π₯ 130 / month Β· β±οΈ 07.12.2018):
pip install datmo
-
git clone https://github.com/comet-ml/examples -
PyPi (π₯ 570K / month Β· π¦ 100 Β· β±οΈ 29.10.2025):
pip install comet_ml -
conda install -c anaconda comet_ml
- <b><a href="https://github.com/catalyst-team/catalyst">Catalyst</a></b> (π₯28 Β· β 3.4K Β· π) - 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> (π₯25 Β· β 2.8K Β· π) - 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> (π₯22 Β· β 1.9K Β· π) - 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> (π₯22 Β· β 560 Β· π€) - SciKit-Learn Laboratory (SKLL) makes it easy to run machine.. <code>βUnlicensed</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> (π₯21 Β· β 630 Β· π) - 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> (π₯21 Β· β 380 Β· π) - 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> (π₯20 Β· β 1.5K Β· π) - 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> (π₯17 Β· 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> (π₯17 Β· β 140 Β· π) - 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> (π₯16 Β· β 320 Β· π) - 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> (π₯15 Β· β 500 Β· π) - 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> (π₯12 Β· β 130 Β· π) - 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> (π₯8 Β· β 12 Β· π) - 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>
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> (π₯45 Β· β 17K) - Development repository for the Triton language and compiler. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>-
GitHub (π¨βπ» 480 Β· π 2.3K Β· π₯ 1.4K Β· π¦ 74K Β· π 2K - 41% open Β· β±οΈ 29.10.2025):
git clone https://github.com/openai/triton -
PyPi (π₯ 41M / month Β· π¦ 540 Β· β±οΈ 13.10.2025):
pip install triton
-
GitHub (π¨βπ» 360 Β· π 3.8K Β· π₯ 25K Β· π¦ 49K Β· π 3.1K - 9% open Β· β±οΈ 29.10.2025):
git clone https://github.com/onnx/onnx -
PyPi (π₯ 13M / month Β· π¦ 1.6K Β· β±οΈ 10.10.2025):
pip install onnx -
Conda (π₯ 2.1M Β· β±οΈ 11.10.2025):
conda install -c conda-forge onnx
-
GitHub (π¨βπ» 280 Β· π 830 Β· π 1.3K - 11% open Β· β±οΈ 30.10.2025):
git clone https://github.com/huggingface/huggingface_hub -
PyPi (π₯ 120M / month Β· π¦ 4.1K Β· β±οΈ 28.10.2025):
pip install huggingface_hub -
Conda (π₯ 4.2M Β· β±οΈ 28.10.2025):
conda install -c conda-forge huggingface_hub
-
GitHub (π¨βπ» 260 Β· π 880 Β· π₯ 95 Β· π¦ 2.8K Β· π 1.1K - 11% open Β· β±οΈ 29.10.2025):
git clone https://github.com/bentoml/BentoML -
PyPi (π₯ 180K / month Β· π¦ 44 Β· β±οΈ 29.10.2025):
pip install bentoml
-
GitHub (π¨βπ» 200 Β· π 710 Β· π₯ 15K Β· π¦ 5.1K Β· π 1.6K - 26% open Β· β±οΈ 22.09.2025):
git clone https://github.com/apple/coremltools -
PyPi (π₯ 1.1M / month Β· π¦ 110 Β· β±οΈ 28.07.2025):
pip install coremltools -
Conda (π₯ 110K Β· β±οΈ 02.10.2025):
conda install -c conda-forge coremltools
-
GitHub (π¨βπ» 220 Β· π 890 Β· π₯ 8K Β· π¦ 900 Β· π 1.7K - 25% open Β· β±οΈ 17.03.2025):
git clone https://github.com/pytorch/serve -
PyPi (π₯ 97K / month Β· π¦ 26 Β· β±οΈ 30.09.2024):
pip install torchserve -
Conda (π₯ 570K Β· β±οΈ 25.03.2025):
conda install -c pytorch torchserve -
Docker Hub (π₯ 1.5M Β· β 32 Β· β±οΈ 30.09.2024):
docker pull pytorch/torchserve
-
GitHub (π¨βπ» 82 Β· π 440 Β· π¦ 51 Β· π 480 - 41% open Β· β±οΈ 20.10.2025):
git clone https://github.com/fastmachinelearning/hls4ml -
PyPi (π₯ 1.7K / month Β· π¦ 1 Β· β±οΈ 17.03.2025):
pip install hls4ml -
Conda (π₯ 12K Β· β±οΈ 22.04.2025):
conda install -c conda-forge hls4ml
-
GitHub (π¨βπ» 86 Β· π 960 Β· π₯ 4K Β· π¦ 160 Β· π 630 - 53% open Β· β±οΈ 07.08.2025):
git clone https://github.com/Microsoft/MMdnn -
PyPi (π₯ 320 / month Β· β±οΈ 24.07.2020):
pip install mmdnn
-
GitHub (π¨βπ» 40 Β· π 290 Β· π₯ 930 Β· π 330 - 21% open Β· β±οΈ 17.07.2025):
git clone https://github.com/microsoft/hummingbird -
PyPi (π₯ 7.6K / month Β· π¦ 7 Β· β±οΈ 25.10.2024):
pip install hummingbird-ml -
Conda (π₯ 64K Β· β±οΈ 22.04.2025):
conda install -c conda-forge hummingbird-ml
-
GitHub (π¨βπ» 4 Β· π 38 Β· π 34 - 32% open Β· β±οΈ 04.01.2025):
git clone https://github.com/riga/tfdeploy -
PyPi (π₯ 100 / month Β· β±οΈ 30.03.2017):
pip install tfdeploy
- <b><a href="https://github.com/BayesWitnesses/m2cgen">m2cgen</a></b> (π₯25 Β· β 2.9K Β· π) - 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> (π₯23 Β· β 1.3K Β· π) - 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> (π₯22 Β· β 8K Β· π) - 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> (π₯21 Β· β 8.4K Β· π) - 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> (π₯20 Β· 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> (π₯19 Β· β 860 Β· π) - 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> (π₯19 Β· β 340) - Represent trained machine learning models as Pyomo optimization.. <code>βUnlicensed</code>
- <b><a href="https://github.com/Cornerstone-OnDemand/modelkit">modelkit</a></b> (π₯17 Β· β 150 Β· π) - 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> (π₯14 Β· β 240 Β· π) - 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> (π₯13 Β· β 2.7K Β· π) - Reference implementation of the Transformer.. <code>βUnlicensed</code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
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> (π₯42 Β· 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 (π¨βπ» 280 Β· π 3.4K Β· π¦ 36K Β· π 2.7K - 23% open Β· β±οΈ 30.10.2025):
git clone https://github.com/slundberg/shap -
PyPi (π₯ 9.5M / month Β· π¦ 1.2K Β· β±οΈ 14.10.2025):
pip install shap -
Conda (π₯ 7.5M Β· β±οΈ 17.06.2025):
conda install -c conda-forge shap
-
GitHub (π¨βπ» 180 Β· π 460 Β· π₯ 190 Β· π¦ 11K Β· π 900 - 19% open Β· β±οΈ 22.10.2025):
git clone https://github.com/arviz-devs/arviz -
PyPi (π₯ 3.7M / month Β· π¦ 410 Β· β±οΈ 09.07.2025):
pip install arviz -
Conda (π₯ 2.5M Β· β±οΈ 10.07.2025):
conda install -c conda-forge arviz
-
GitHub (π¨βπ» 2 Β· π 3K Β· π₯ 160K Β· π¦ 13 Β· π 1.2K - 1% open Β· β±οΈ 29.10.2025):
git clone https://github.com/lutzroeder/netron -
PyPi (π₯ 43K / month Β· π¦ 92 Β· β±οΈ 23.10.2025):
pip install netron
-
GitHub (π¨βπ» 130 Β· π 290 Β· π¦ 24K Β· π 390 - 62% open Β· β±οΈ 25.09.2025):
git clone https://github.com/huggingface/evaluate -
PyPi (π₯ 3.6M / month Β· π¦ 660 Β· β±οΈ 18.09.2025):
pip install evaluate
-
GitHub (π¨βπ» 53 Β· π 770 Β· π¦ 930 Β· π 490 - 22% open Β· β±οΈ 24.10.2025):
git clone https://github.com/interpretml/interpret -
PyPi (π₯ 230K / month Β· π¦ 58 Β· β±οΈ 14.10.2025):
pip install interpret
-
GitHub (π¨βπ» 140 Β· π 540 Β· π¦ 3.5K Β· π 610 - 41% open Β· β±οΈ 23.10.2025):
git clone https://github.com/pytorch/captum -
PyPi (π₯ 330K / month Β· π¦ 170 Β· β±οΈ 27.03.2025):
pip install captum -
Conda (π₯ 130K Β· β±οΈ 22.04.2025):
conda install -c conda-forge captum
-
GitHub (π¨βπ» 100 Β· π 980 Β· π₯ 43 Β· π¦ 660 Β· π 510 - 27% open Β· β±οΈ 28.10.2025):
git clone https://github.com/py-why/dowhy -
PyPi (π₯ 83K / month Β· π¦ 28 Β· β±οΈ 12.07.2025):
pip install dowhy -
Conda (π₯ 51K Β· β±οΈ 13.07.2025):
conda install -c conda-forge dowhy
-
GitHub (π¨βπ» 43 Β· π 350 Β· π¦ 200 Β· π 240 - 16% open Β· β±οΈ 03.10.2025):
git clone https://github.com/MAIF/shapash -
PyPi (π₯ 7.5K / month Β· π¦ 4 Β· β±οΈ 24.07.2025):
pip install shapash
-
GitHub (π¨βπ» 23 Β· π 340 Β· π¦ 650 Β· π 240 - 16% open Β· β±οΈ 01.08.2025):
git clone https://github.com/oegedijk/explainerdashboard -
PyPi (π₯ 42K / month Β· π¦ 15 Β· β±οΈ 03.06.2025):
pip install explainerdashboard -
Conda (π₯ 75K Β· β±οΈ 04.06.2025):
conda install -c conda-forge explainerdashboard
-
GitHub (π¨βπ» 100 Β· π 470 Β· π¦ 3 Β· π 520 - 24% open Β· β±οΈ 27.10.2025):
git clone https://github.com/fairlearn/fairlearn -
PyPi (π₯ 160K / month Β· π¦ 80 Β· β±οΈ 19.10.2025):
pip install fairlearn -
Conda (π₯ 55K Β· β±οΈ 22.04.2025):
conda install -c conda-forge fairlearn
-
GitHub (π¨βπ» 27 Β· π 340 Β· π¦ 1.6K Β· π 210 - 35% open Β· β±οΈ 06.03.2025):
git clone https://github.com/parrt/dtreeviz -
PyPi (π₯ 110K / month Β· π¦ 53 Β· β±οΈ 07.07.2022):
pip install dtreeviz -
Conda (π₯ 120K Β· β±οΈ 22.04.2025):
conda install -c conda-forge dtreeviz
-
GitHub (π¨βπ» 61 Β· π 280 Β· π 97 - 39% open Β· β±οΈ 06.08.2025):
git clone https://github.com/tensorflow/model-analysis -
PyPi (π₯ 200K / month Β· π¦ 20 Β· β±οΈ 23.06.2025):
pip install tensorflow-model-analysis
-
GitHub (π¨βπ» 73 Β· π 870 Β· π¦ 740 Β· π 300 - 65% open Β· β±οΈ 16.10.2025):
git clone https://github.com/Trusted-AI/AIF360 -
PyPi (π₯ 29K / month Β· π¦ 32 Β· β±οΈ 08.04.2024):
pip install aif360 -
Conda (π₯ 29K Β· β±οΈ 22.04.2025):
conda install -c conda-forge aif360
-
GitHub (π¨βπ» 27 Β· π 130 Β· π¦ 130 Β· π 98 - 38% open Β· β±οΈ 26.08.2025):
git clone https://github.com/csinva/imodels -
PyPi (π₯ 30K / month Β· π¦ 12 Β· β±οΈ 26.08.2025):
pip install imodels
-
GitHub (π¨βπ» 38 Β· π 360 Β· π 210 - 57% open Β· β±οΈ 20.12.2024):
git clone https://github.com/PAIR-code/lit -
PyPi (π₯ 11K / month Β· π¦ 3 Β· β±οΈ 20.12.2024):
pip install lit-nlp -
Conda (π₯ 130K Β· β±οΈ 22.04.2025):
conda install -c conda-forge lit-nlp
-
GitHub (π¨βπ» 43 Β· π 430 Β· π 330 - 28% open Β· β±οΈ 07.02.2025):
git clone https://github.com/microsoft/responsible-ai-toolbox -
PyPi (π₯ 10K / month Β· π¦ 6 Β· β±οΈ 08.07.2024):
pip install raiwidgets
-
GitHub (π¨βπ» 23 Β· π 120 Β· π¦ 200 Β· π 99 - 51% open Β· β±οΈ 25.03.2025):
git clone https://github.com/dssg/aequitas -
PyPi (π₯ 19K / month Β· π¦ 8 Β· β±οΈ 30.01.2024):
pip install aequitas
-
GitHub (π¨βπ» 41 Β· π 310 Β· π¦ 170 Β· π 86 - 62% open Β· β±οΈ 26.02.2025):
git clone https://github.com/Trusted-AI/AIX360 -
PyPi (π₯ 1.8K / month Β· π¦ 1 Β· β±οΈ 31.07.2023):
pip install aix360
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GitHub (π¨βπ» 17 Β· π 190 Β· π¦ 260 Β· π 89 - 3% open Β· β±οΈ 07.04.2025):
git clone https://github.com/philipperemy/keract -
PyPi (π₯ 8.8K / month Β· π¦ 7 Β· β±οΈ 07.04.2025):
pip install keract
-
GitHub (π¨βπ» 23 Β· π 210 Β· π 190 - 49% open Β· β±οΈ 13.07.2025):
git clone https://github.com/interpretml/DiCE -
PyPi (π₯ 48K / month Β· π¦ 13 Β· β±οΈ 13.07.2025):
pip install dice-ml
-
GitHub (π¨βπ» 6 Β· π 87 Β· π¦ 42 Β· π 30 - 13% open Β· β±οΈ 14.02.2025):
git clone https://github.com/aerdem4/lofo-importance -
PyPi (π₯ 1.5K / month Β· π¦ 5 Β· β±οΈ 14.02.2025):
pip install lofo-importance
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GitHub (π¨βπ» 16 Β· π 130 Β· π 39 - 20% open Β· β±οΈ 24.03.2025):
git clone https://github.com/parrt/random-forest-importances -
PyPi (π₯ 16K / month Β· π¦ 5 Β· β±οΈ 28.01.2021):
pip install rfpimp
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GitHub (π¨βπ» 39 Β· π 86 Β· π 45 - 77% open Β· β±οΈ 04.08.2025):
git clone https://github.com/tensorflow/fairness-indicators -
PyPi (π₯ 1.1K / month Β· β±οΈ 25.06.2025):
pip install fairness-indicators
- <b><a href="https://github.com/marcotcr/lime">Lime</a></b> (π₯32 Β· β 12K Β· π) - 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> (π₯29 Β· β 1.8K Β· π) - 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> (π₯27 Β· β 4.4K Β· π) - 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> (π₯27 Β· β 3.9K) - Deepchecks: Tests for Continuous Validation of ML Models &.. <code><a href="http://bit.ly/3pwmjO5">βοΈAGPL-3.0</a></code>
- <b><a href="https://github.com/SeldonIO/alibi">Alibi</a></b> (π₯27 Β· β 2.6K) - Algorithms for explaining machine learning models. <code><a href="https://tldrlegal.com/search?q=Intel">βοΈIntel</a></code>
- <b><a href="https://github.com/reiinakano/scikit-plot">scikit-plot</a></b> (π₯27 Β· β 2.4K Β· π) - 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> (π₯27 Β· β 1.4K) - moDel Agnostic Language for Exploration and eXplanation (JMLR 2018;.. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/TeamHG-Memex/eli5">eli5</a></b> (π₯26 Β· β 2.8K Β· π) - 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> (π₯26 Β· β 1.3K Β· π) - 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> (π₯25 Β· β 4.7K Β· π) - 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> (π₯25 Β· β 3K Β· π) - 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> (π₯24 Β· β 2.4K Β· π) - 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> (π₯24 Β· β 2K Β· π) - 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> (π₯23 Β· β 980 Β· π) - 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> (π₯22 Β· β 1K Β· π) - 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> (π₯22 Β· β 870 Β· π) - 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> (π₯22 Β· β 760 Β· π) - 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> (π₯22 Β· β 630) - Quantus is an eXplainable AI toolkit for responsible evaluation of.. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/EthicalML/xai">XAI</a></b> (π₯21 Β· β 1.2K Β· π) - 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> (π₯20 Β· β 640 Β· π) - 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> (π₯19 Β· β 2.1K Β· π) - 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> (π₯17 Β· β 460 Β· π) - 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> (π₯17 Β· β 440 Β· π) - 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> (π₯16 Β· β 810 Β· π) - 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> (π₯15 Β· β 740 Β· π) - 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> (π₯15 Β· β 440 Β· π) - 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> (π₯15 Β· 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> (π₯14 Β· β 1.1K) - Python Library for Model Interpretation/Explanations. <code><a href="https://tldrlegal.com/search?q=UPL-1.0">βοΈUPL-1.0</a></code>
- <b><a href="https://github.com/interpretml/interpret-text">interpret-text</a></b> (π₯14 Β· β 430 Β· π) - 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> (π₯13 Β· β 45 Β· π) - 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> (π₯12 Β· β 120 Β· π) - 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> (π₯12 Β· β 87 Β· π) - Contextual AI adds explainability to different stages of.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
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.
πΒ <b><a href="https://github.com/erikbern/ann-benchmarks">ANN Benchmarks</a></b> ( β 5.5K) - Benchmarks of approximate nearest neighbor libraries in Python.
<details><summary><b><a href="https://github.com/milvus-io/milvus">Milvus</a></b> (π₯43 Β· 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 (π¨βπ» 330 Β· π 3.5K Β· π₯ 290K Β· π 15K - 5% open Β· β±οΈ 30.10.2025):
git clone https://github.com/milvus-io/milvus -
PyPi (π₯ 3.3M / month Β· π¦ 350 Β· β±οΈ 19.09.2025):
pip install pymilvus -
Docker Hub (π₯ 72M Β· β 90 Β· β±οΈ 30.10.2025):
docker pull milvusdb/milvus
-
GitHub (π¨βπ» 260 Β· π 4K Β· π¦ 5K Β· π 2.7K - 9% open Β· β±οΈ 30.10.2025):
git clone https://github.com/facebookresearch/faiss -
PyPi (π₯ 3.3M / month Β· π¦ 350 Β· β±οΈ 19.09.2025):
pip install pymilvus -
Conda (π₯ 3M Β· β±οΈ 22.04.2025):
conda install -c conda-forge faiss
-
GitHub (π¨βπ» 90 Β· π 1.2K Β· π¦ 5.4K Β· π 420 - 16% open Β· β±οΈ 29.10.2025):
git clone https://github.com/spotify/annoy -
PyPi (π₯ 1M / month Β· π¦ 200 Β· β±οΈ 14.06.2023):
pip install annoy -
Conda (π₯ 800K Β· β±οΈ 01.09.2025):
conda install -c conda-forge python-annoy
-
GitHub (π¨βπ» 81 Β· π 230 Β· π₯ 110K Β· π¦ 210 Β· π 250 - 32% open Β· β±οΈ 29.10.2025):
git clone https://github.com/unum-cloud/usearch -
PyPi (π₯ 140K / month Β· π¦ 44 Β· β±οΈ 04.09.2025):
pip install usearch -
npm (π₯ 18K / month Β· π¦ 23 Β· β±οΈ 29.10.2025):
npm install usearch -
Docker Hub (π₯ 480 Β· β 1 Β· β±οΈ 29.10.2025):
docker pull unum/usearch
-
GitHub (π¨βπ» 49 Β· π 460 Β· π¦ 1.4K Β· π 440 - 20% open Β· β±οΈ 22.10.2025):
git clone https://github.com/nmslib/nmslib -
PyPi (π₯ 280K / month Β· π¦ 67 Β· β±οΈ 23.10.2025):
pip install nmslib -
Conda (π₯ 230K Β· β±οΈ 30.08.2025):
conda install -c conda-forge nmslib
-
GitHub (π¨βπ» 31 Β· π 110 Β· π¦ 13K Β· π 140 - 53% open Β· β±οΈ 17.10.2025):
git clone https://github.com/lmcinnes/pynndescent -
PyPi (π₯ 2.5M / month Β· π¦ 160 Β· β±οΈ 17.06.2024):
pip install pynndescent -
Conda (π₯ 2.5M Β· β±οΈ 22.04.2025):
conda install -c conda-forge pynndescent
-
GitHub (π¨βπ» 19 Β· π 120 Β· π 150 - 18% open Β· β±οΈ 15.10.2025):
git clone https://github.com/yahoojapan/NGT -
PyPi (π₯ 1.8K / month Β· π¦ 12 Β· β±οΈ 26.02.2025):
pip install ngt
- <b><a href="https://github.com/nmslib/hnswlib">hnswlib</a></b> (π₯32 Β· β 5K Β· π) - 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> (π₯22 Β· β 770 Β· π) - 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> (π₯22 Β· β 580 Β· π) - 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> (π₯20 Β· β 1.7K Β· π) - 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> (π₯11 Β· β 920 Β· π) - Approximate Nearest Neighbor Search for Sparse Data in Python!. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
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> (π₯40 Β· β 9.3K) - Bayesian Modeling and Probabilistic Programming in Python. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>-
GitHub (π¨βπ» 530 Β· π 2.1K Β· π₯ 140 Β· π¦ 7.7K Β· π 3.6K - 11% open Β· β±οΈ 28.10.2025):
git clone https://github.com/pymc-devs/pymc -
PyPi (π₯ 330K / month Β· π¦ 190 Β· β±οΈ 31.05.2024):
pip install pymc3 -
Conda (π₯ 860K Β· β±οΈ 22.04.2025):
conda install -c conda-forge pymc3
-
GitHub (π¨βπ» 500 Β· π 1.1K Β· π¦ 4 Β· π 1.5K - 48% open Β· β±οΈ 22.10.2025):
git clone https://github.com/tensorflow/probability -
PyPi (π₯ 880K / month Β· π¦ 620 Β· β±οΈ 08.11.2024):
pip install tensorflow-probability -
Conda (π₯ 200K Β· β±οΈ 22.04.2025):
conda install -c conda-forge tensorflow-probability
-
GitHub (π¨βπ» 140 Β· π 580 Β· π¦ 3.2K Β· π 1.4K - 28% open Β· β±οΈ 14.10.2025):
git clone https://github.com/cornellius-gp/gpytorch -
PyPi (π₯ 500K / month Β· π¦ 250 Β· β±οΈ 14.10.2025):
pip install gpytorch -
Conda (π₯ 230K Β· β±οΈ 18.10.2025):
conda install -c conda-forge gpytorch
-
GitHub (π¨βπ» 180 Β· π 860 Β· π₯ 680 Β· π¦ 1.7K Β· π 1.1K - 27% open Β· β±οΈ 29.10.2025):
git clone https://github.com/pgmpy/pgmpy -
PyPi (π₯ 120K / month Β· π¦ 72 Β· β±οΈ 31.03.2025):
pip install pgmpy
-
GitHub (π¨βπ» 23 Β· π 100 Β· π¦ 130K Β· π 160 - 46% open Β· β±οΈ 20.10.2025):
git clone https://github.com/pydata/patsy -
PyPi (π₯ 22M / month Β· π¦ 680 Β· β±οΈ 20.10.2025):
pip install patsy -
Conda (π₯ 19M Β· β±οΈ 20.10.2025):
conda install -c conda-forge patsy
-
GitHub (π¨βπ» 160 Β· π 1K Β· π 1.1K - 24% open Β· β±οΈ 09.07.2025):
git clone https://github.com/pyro-ppl/pyro -
PyPi (π₯ 630K / month Β· π¦ 190 Β· β±οΈ 02.06.2024):
pip install pyro-ppl -
Conda (π₯ 280K Β· β±οΈ 22.04.2025):
conda install -c conda-forge pyro-ppl
-
GitHub (π¨βπ» 54 Β· π 250 Β· π¦ 1.6K Β· π 350 - 18% open Β· β±οΈ 12.10.2025):
git clone https://github.com/SALib/SALib -
PyPi (π₯ 250K / month Β· π¦ 190 Β· β±οΈ 12.10.2025):
pip install salib -
Conda (π₯ 290K Β· β±οΈ 12.10.2025):
conda install -c conda-forge salib
-
GitHub (π¨βπ» 49 Β· π 740 Β· π¦ 3.7K Β· π 450 - 16% open Β· β±οΈ 31.10.2024):
git clone https://github.com/hmmlearn/hmmlearn -
PyPi (π₯ 240K / month Β· π¦ 92 Β· β±οΈ 31.10.2024):
pip install hmmlearn -
Conda (π₯ 430K Β· β±οΈ 10.09.2025):
conda install -c conda-forge hmmlearn
-
GitHub (π¨βπ» 76 Β· π 430 Β· π¦ 3.2K Β· π 300 - 19% open Β· β±οΈ 14.10.2025):
git clone https://github.com/dfm/emcee -
PyPi (π₯ 170K / month Β· π¦ 440 Β· β±οΈ 19.04.2024):
pip install emcee -
Conda (π₯ 510K Β· β±οΈ 22.04.2025):
conda install -c conda-forge emcee
-
GitHub (π¨βπ» 84 Β· π 430 Β· π¦ 790 Β· π 840 - 19% open Β· β±οΈ 29.05.2025):
git clone https://github.com/GPflow/GPflow -
PyPi (π₯ 32K / month Β· π¦ 43 Β· β±οΈ 29.05.2025):
pip install gpflow -
Conda (π₯ 51K Β· β±οΈ 22.04.2025):
conda install -c conda-forge gpflow
-
GitHub (π¨βπ» 47 Β· π 140 Β· π¦ 220 Β· π 460 - 21% open Β· β±οΈ 24.10.2025):
git clone https://github.com/bambinos/bambi -
PyPi (π₯ 48K / month Β· π¦ 19 Β· β±οΈ 24.10.2025):
pip install bambi -
Conda (π₯ 56K Β· β±οΈ 27.10.2025):
conda install -c conda-forge bambi
-
GitHub (π¨βπ» 75 Β· π 590 Β· π 800 - 4% open Β· β±οΈ 07.02.2025):
git clone https://github.com/jmschrei/pomegranate -
PyPi (π₯ 36K / month Β· π¦ 67 Β· β±οΈ 07.02.2025):
pip install pomegranate -
Conda (π₯ 230K Β· β±οΈ 22.04.2025):
conda install -c conda-forge pomegranate
-
GitHub (π¨βπ» 18 Β· π 41 Β· π₯ 67 Β· π¦ 1.2K Β· π 72 - 6% open Β· β±οΈ 11.09.2025):
git clone https://github.com/maximtrp/scikit-posthocs -
PyPi (π₯ 120K / month Β· π¦ 73 Β· β±οΈ 29.03.2025):
pip install scikit-posthocs -
Conda (π₯ 1.1M Β· β±οΈ 22.04.2025):
conda install -c conda-forge scikit-posthocs
-
GitHub (π¨βπ» 40 Β· π 1.1K):
git clone https://github.com/twopirllc/pandas-ta -
PyPi (π₯ 290K / month Β· π¦ 190 Β· β±οΈ 14.09.2025):
pip install pandas-ta -
Conda (π₯ 39K Β· β±οΈ 23.09.2025):
conda install -c conda-forge pandas-ta
-
GitHub (π¨βπ» 24 Β· π 87 Β· π¦ 67 Β· π 120 - 18% open Β· β±οΈ 07.10.2025):
git clone https://github.com/baal-org/baal -
PyPi (π₯ 1.8K / month Β· π¦ 2 Β· β±οΈ 24.06.2025):
pip install baal -
Conda (π₯ 15K Β· β±οΈ 22.04.2025):
conda install -c conda-forge baal
-
GitHub (π¨βπ» 21 Β· π 140 Β· π 410 - 13% open Β· β±οΈ 05.06.2025):
git clone https://github.com/uber/orbit -
PyPi (π₯ 24K / month Β· π¦ 1 Β· β±οΈ 01.04.2024):
pip install orbit-ml
-
GitHub (π¨βπ» 14 Β· π 170 Β· π¦ 35 Β· π 100 - 39% open Β· β±οΈ 25.01.2025):
git clone https://github.com/mattjj/pyhsmm -
PyPi (π₯ 300 / month Β· π¦ 1 Β· β±οΈ 10.05.2017):
pip install pyhsmm
-
GitHub (π¨βπ» 13 Β· π 35 Β· π 67 - 23% open Β· β±οΈ 31.07.2025):
git clone https://github.com/ENSTA-U2IS-AI/torch-uncertainty -
PyPi (π₯ 920 / month Β· π¦ 4 Β· β±οΈ 31.07.2025):
pip install torch-uncertainty
- <b><a href="https://github.com/rlabbe/filterpy">filterpy</a></b> (π₯31 Β· β 3.7K Β· π) - 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> (π₯29 Β· β 1.8K) - Statistical package in Python based on Pandas. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/blei-lab/edward">Edward</a></b> (π₯27 Β· β 4.8K Β· π) - 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> (π₯27 Β· β 360 Β· π) - 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> (π₯21 Β· β 240 Β· π) - 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> (π₯15 Β· β 2.2K Β· π) - 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>
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> (π₯34 Β· β 5.6K) - Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>-
GitHub (π¨βπ» 140 Β· π 1.2K Β· π¦ 770 Β· π 910 - 1% open Β· β±οΈ 17.10.2025):
git clone https://github.com/Trusted-AI/adversarial-robustness-toolbox -
PyPi (π₯ 29K / month Β· π¦ 25 Β· β±οΈ 07.07.2025):
pip install adversarial-robustness-toolbox -
Conda (π₯ 85K Β· β±οΈ 07.07.2025):
conda install -c conda-forge adversarial-robustness-toolbox
-
GitHub (π¨βπ» 67 Β· π 420 Β· π¦ 430 Β· π 290 - 23% open Β· β±οΈ 10.07.2025):
git clone https://github.com/QData/TextAttack -
PyPi (π₯ 9.1K / month Β· π¦ 11 Β· β±οΈ 11.03.2024):
pip install textattack -
Conda (π₯ 11K Β· β±οΈ 22.04.2025):
conda install -c conda-forge textattack
- <b><a href="https://github.com/cleverhans-lab/cleverhans">CleverHans</a></b> (π₯29 Β· β 6.4K Β· π) - 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> (π₯28 Β· β 2.9K Β· π) - 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> (π₯24 Β· β 1.4K Β· π) - A Toolbox for Adversarial Robustness Research. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-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> (π₯20 Β· β 950 Β· π) - 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> (π₯19 Β· β 1.4K Β· π) - 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> (π₯17 Β· β 650 Β· π) - Unified Multilingual Robustness Evaluation Toolkit for.. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/airbnb/artificial-adversary">Adversary</a></b> (π₯15 Β· β 400 Β· π) - Tool to generate adversarial text examples and test machine.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
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> (π₯37 Β· β 3.1K) - Accelerate inference and training of Transformers, Diffusers, TIMM.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>-
GitHub (π¨βπ» 150 Β· π 600 Β· π¦ 6.3K Β· π 860 - 30% open Β· β±οΈ 30.10.2025):
git clone https://github.com/huggingface/optimum -
PyPi (π₯ 3.7M / month Β· π¦ 270 Β· β±οΈ 09.10.2025):
pip install optimum -
Conda (π₯ 50K Β· β±οΈ 09.10.2025):
conda install -c conda-forge optimum
-
GitHub (π¨βπ» 310 Β· π 980 Β· π¦ 64 Β· π 7.3K - 15% open Β· β±οΈ 30.10.2025):
git clone https://github.com/rapidsai/cudf -
PyPi (π₯ 2.8K / month Β· π¦ 22 Β· β±οΈ 01.06.2020):
pip install cudf
-
GitHub (π¨βπ» 83 Β· π 300 Β· π¦ 4K Β· π 290 - 29% open Β· β±οΈ 12.10.2025):
git clone https://github.com/inducer/pycuda -
PyPi (π₯ 66K / month Β· π¦ 200 Β· β±οΈ 09.09.2025):
pip install pycuda -
Conda (π₯ 1.1M Β· β±οΈ 27.10.2025):
conda install -c conda-forge pycuda
-
GitHub (π¨βπ» 140 Β· π 1.4K Β· π¦ 3.3K Β· π 1.3K - 57% open Β· β±οΈ 29.10.2025):
git clone https://github.com/NVIDIA/apex -
Conda (π₯ 580K Β· β±οΈ 26.07.2025):
conda install -c conda-forge nvidia-apex
-
GitHub (π¨βπ» 190 Β· π 600 Β· π 3K - 31% open Β· β±οΈ 30.10.2025):
git clone https://github.com/rapidsai/cuml -
PyPi (π₯ 2.5K / month Β· π¦ 14 Β· β±οΈ 01.06.2020):
pip install cuml
-
GitHub (π¨βπ» 17 Β· π 280 Β· π¦ 7.9K Β· π 130 - 22% open Β· β±οΈ 13.04.2025):
git clone https://github.com/wookayin/gpustat -
PyPi (π₯ 1.1M / month Β· π¦ 150 Β· β±οΈ 22.08.2023):
pip install gpustat -
Conda (π₯ 310K Β· β±οΈ 22.04.2025):
conda install -c conda-forge gpustat
-
GitHub (π¨βπ» 97 Β· π 540 Β· π₯ 9.6K Β· π 1.8K - 19% open Β· β±οΈ 28.07.2025):
git clone https://github.com/arrayfire/arrayfire -
PyPi (π₯ 4.5K / month Β· π¦ 13 Β· β±οΈ 22.02.2022):
pip install arrayfire
-
GitHub (π¨βπ» 120 Β· π 340 Β· π 1.9K - 6% open Β· β±οΈ 29.10.2025):
git clone https://github.com/rapidsai/cugraph -
PyPi (π₯ 550 / month Β· π¦ 4 Β· β±οΈ 01.06.2020):
pip install cugraph -
Conda (π₯ 69K Β· β±οΈ 22.04.2025):
conda install -c conda-forge libcugraph
-
GitHub (π¨βπ» 340 Β· π 950):
git clone https://github.com/cupy/cupy -
PyPi (π₯ 39K / month Β· π¦ 400 Β· β±οΈ 18.08.2025):
pip install cupy -
Conda (π₯ 7.2M Β· β±οΈ 14.09.2025):
conda install -c conda-forge cupy -
Docker Hub (π₯ 92K Β· β 14 Β· β±οΈ 18.08.2025):
docker pull cupy/cupy
-
GitHub (π¨βπ» 99 Β· π 650 Β· π 1.7K - 15% open Β· β±οΈ 30.10.2025):
git clone https://github.com/NVIDIA/DALI
-
GitHub (π¨βπ» 35 Β· π 160 Β· π₯ 700 Β· π 230 - 32% open Β· β±οΈ 05.10.2025):
git clone https://github.com/KomputeProject/kompute -
PyPi (π₯ 1.8K / month Β· β±οΈ 20.01.2024):
pip install kp
- <b><a href="https://github.com/anderskm/gputil">GPUtil</a></b> (π₯25 Β· β 1.2K Β· π) - 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> (π₯25 Β· β 990 Β· π) - 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> (π₯22 Β· β 250 Β· π) - 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> (π₯20 Β· β 2K Β· π) - 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> (π₯20 Β· β 860 Β· π) - 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> (π₯18 Β· β 140 Β· π) - 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> (π₯15 Β· β 680 Β· π) - 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> (π₯15 Β· β 220 Β· π) - 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> (π₯14 Β· β 730 Β· π) - GPU accelerated signal processing. <code>βUnlicensed</code>
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> (π₯39 Β· 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 (π¨βπ» 660 Β· π 1.6K Β· π¦ 25K Β· π 1.5K - 47% open Β· β±οΈ 17.10.2025):
git clone https://github.com/tensorflow/datasets -
PyPi (π₯ 1.8M / month Β· π¦ 340 Β· β±οΈ 28.05.2025):
pip install tensorflow-datasets -
Conda (π₯ 51K Β· β±οΈ 22.04.2025):
conda install -c conda-forge tensorflow-datasets
-
GitHub (π¨βπ» 110 Β· π 1.7K Β· π 710 - 2% open Β· β±οΈ 17.01.2025):
git clone https://github.com/tensorflow/hub -
PyPi (π₯ 2M / month Β· π¦ 300 Β· β±οΈ 30.01.2024):
pip install tensorflow-hub -
Conda (π₯ 130K Β· β±οΈ 22.04.2025):
conda install -c conda-forge tensorflow-hub
-
GitHub (π¨βπ» 200 Β· π 710 Β· π¦ 1.8K Β· π 1.2K - 22% open Β· β±οΈ 26.03.2025):
git clone https://github.com/tensorflow/tfx -
PyPi (π₯ 37K / month Β· π¦ 17 Β· β±οΈ 11.12.2024):
pip install tfx
-
GitHub (π¨βπ» 87 Β· π 320 Β· π 400 - 57% open Β· β±οΈ 07.07.2025):
git clone https://github.com/tensorflow/model-optimization -
PyPi (π₯ 920K / month Β· π¦ 45 Β· β±οΈ 08.02.2024):
pip install tensorflow-model-optimization
-
GitHub (π¨βπ» 120 Β· π 290 Β· π 660 - 44% open Β· β±οΈ 10.04.2025):
git clone https://github.com/tensorflow/io -
PyPi (π₯ 730K / month Β· π¦ 61 Β· β±οΈ 01.07.2024):
pip install tensorflow-io
-
GitHub (π¨βπ» 31 Β· π 220 Β· π 220 - 17% open Β· β±οΈ 06.08.2025):
git clone https://github.com/tensorflow/transform -
PyPi (π₯ 250K / month Β· π¦ 19 Β· β±οΈ 13.06.2025):
pip install tensorflow-transform
-
GitHub (π¨βπ» 39 Β· π 190 Β· π¦ 520 Β· π 69 - 1% open Β· β±οΈ 29.01.2025):
git clone https://github.com/tensorflow/neural-structured-learning -
PyPi (π₯ 3.2K / month Β· π¦ 3 Β· β±οΈ 29.07.2022):
pip install neural-structured-learning
-
GitHub (π¨βπ» 29 Β· π 92 Β· π 100 - 73% open Β· β±οΈ 01.10.2025):
git clone https://github.com/tensorflow/cloud -
PyPi (π₯ 18K / month Β· π¦ 7 Β· β±οΈ 17.06.2021):
pip install tensorflow-cloud
-
GitHub (π¨βπ» 24 Β· π 260 Β· π 100 - 10% open Β· β±οΈ 19.08.2025):
git clone https://github.com/tensorflow/compression -
PyPi (π₯ 4.3K / month Β· π¦ 2 Β· β±οΈ 02.02.2024):
pip install tensorflow-compression
- <b><a href="https://github.com/tensorflow/tensor2tensor">tensor2tensor</a></b> (π₯33 Β· β 17K Β· π) - 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> (π₯32 Β· β 1.7K Β· π) - 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> (π₯28 Β· β 1K Β· π) - 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> (π₯26 Β· β 2.1K Β· π) - 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> (π₯22 Β· β 980 Β· π) - 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> (π₯21 Β· β 1K Β· π) - 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> (π₯18 Β· β 780 Β· π) - 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>
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> (π₯33 Β· 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 (π¨βπ» 81 Β· π 170 Β· π¦ 1.4K Β· π 610 - 35% open Β· β±οΈ 29.10.2025):
git clone https://github.com/patrick-kidger/equinox -
PyPi (π₯ 500K / month Β· π¦ 350 Β· β±οΈ 09.10.2025):
pip install equinox
- <b><a href="https://github.com/google/evojax">evojax</a></b> (π₯18 Β· β 920 Β· π) - 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> (π₯12 Β· β 130 Β· π) - A JAX-based research framework for writing differentiable.. <code><a href="http://bit.ly/37RvQcA">βοΈLGPL-3.0</a></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code>
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> (π₯35 Β· 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 (π¨βπ» 86 Β· π 180 Β· π¦ 14K Β· π 250 - 15% open Β· β±οΈ 28.10.2025):
git clone https://github.com/intel/scikit-learn-intelex -
PyPi (π₯ 89K / month Β· π¦ 74 Β· β±οΈ 22.10.2025):
pip install scikit-learn-intelex -
Conda (π₯ 650K Β· β±οΈ 30.10.2025):
conda install -c conda-forge scikit-learn-intelex
-
GitHub (π¨βπ» 89 Β· π 1.3K Β· π 630 - 8% open Β· β±οΈ 14.08.2025):
git clone https://github.com/scikit-learn-contrib/imbalanced-learn -
PyPi (π₯ 14M / month Β· π¦ 600 Β· β±οΈ 14.08.2025):
pip install imbalanced-learn -
Conda (π₯ 750K Β· β±οΈ 14.08.2025):
conda install -c conda-forge imbalanced-learn
-
GitHub (π¨βπ» 110 Β· π 880 Β· π¦ 21K Β· π 500 - 29% open Β· β±οΈ 19.06.2025):
git clone https://github.com/rasbt/mlxtend -
PyPi (π₯ 960K / month Β· π¦ 200 Β· β±οΈ 26.01.2025):
pip install mlxtend -
Conda (π₯ 460K Β· β±οΈ 22.04.2025):
conda install -c conda-forge mlxtend
-
GitHub (π¨βπ» 71 Β· π 400 Β· π¦ 4.1K Β· π 300 - 13% open Β· β±οΈ 24.03.2025):
git clone https://github.com/scikit-learn-contrib/category_encoders -
PyPi (π₯ 2.1M / month Β· π¦ 310 Β· β±οΈ 15.03.2025):
pip install category_encoders -
Conda (π₯ 370K Β· β±οΈ 22.04.2025):
conda install -c conda-forge category_encoders
-
GitHub (π¨βπ» 69 Β· π 120 Β· π¦ 190 Β· π 340 - 9% open Β· β±οΈ 21.10.2025):
git clone https://github.com/koaning/scikit-lego -
PyPi (π₯ 53K / month Β· π¦ 13 Β· β±οΈ 15.09.2025):
pip install scikit-lego -
Conda (π₯ 76K Β· β±οΈ 22.04.2025):
conda install -c conda-forge scikit-lego
-
GitHub (π¨βπ» 24 Β· π 1.1K Β· π¦ 280 Β· π 180 - 37% open Β· β±οΈ 31.08.2025):
git clone https://github.com/guofei9987/scikit-opt -
PyPi (π₯ 9.1K / month Β· π¦ 15 Β· β±οΈ 14.01.2022):
pip install scikit-opt
-
GitHub (π¨βπ» 7 Β· π 75 Β· π¦ 620 Β· π 27 - 7% open Β· β±οΈ 12.10.2024):
git clone https://github.com/trent-b/iterative-stratification -
PyPi (π₯ 54K / month Β· π¦ 15 Β· β±οΈ 12.10.2024):
pip install iterative-stratification
-
GitHub (π¨βπ» 7 Β· π 54 Β· π¦ 93 Β· π 23 - 17% open Β· β±οΈ 28.10.2025):
git clone https://github.com/scikit-tda/scikit-tda -
PyPi (π₯ 1.8K / month Β· β±οΈ 19.07.2024):
pip install scikit-tda
- <b><a href="https://github.com/sebp/scikit-survival">scikit-survival</a></b> (π₯32 Β· β 1.2K) - Survival analysis built on top of scikit-learn. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-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> (π₯27 Β· β 1.3K Β· π) - 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> (π₯27 Β· β 950 Β· π) - 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> (π₯25 Β· β 430 Β· π) - 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> (π₯22 Β· β 650 Β· π) - machine learning with logical rules in Python. <code><a href="https://tldrlegal.com/search?q=BSD-1-Clause">βοΈBSD-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> (π₯21 Β· β 660 Β· π) - (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> (π₯21 Β· 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> (π₯20 Β· β 1.8K Β· π) - 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> (π₯18 Β· β 730 Β· π) - 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> (π₯18 Β· β 490 Β· π) - 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> (π₯17 Β· 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>
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> (π₯43 Β· 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 (π¨βπ» 370 Β· π 1.2K Β· π¦ 110K Β· π 1.9K - 5% open Β· β±οΈ 22.10.2025):
git clone https://github.com/huggingface/accelerate -
PyPi (π₯ 17M / month Β· π¦ 2.8K Β· β±οΈ 20.10.2025):
pip install accelerate -
Conda (π₯ 670K Β· β±οΈ 24.10.2025):
conda install -c conda-forge accelerate
-
GitHub (π¨βπ» 420 Β· π 3.6K Β· π¦ 20 Β· π 1K - 12% open Β· β±οΈ 30.10.2025):
git clone https://github.com/geohot/tinygrad
-
GitHub (π¨βπ» 45 Β· π 660 Β· π¦ 2.9K Β· π 530 - 14% open Β· β±οΈ 17.08.2025):
git clone https://github.com/KevinMusgrave/pytorch-metric-learning -
PyPi (π₯ 2.3M / month Β· π¦ 68 Β· β±οΈ 17.08.2025):
pip install pytorch-metric-learning -
Conda (π₯ 13K Β· β±οΈ 25.03.2025):
conda install -c metric-learning pytorch-metric-learning
-
GitHub (π¨βπ» 23 Β· π 940 Β· π¦ 5.5K Β· π 230 - 35% open Β· β±οΈ 04.04.2025):
git clone https://github.com/rtqichen/torchdiffeq -
PyPi (π₯ 1M / month Β· π¦ 120 Β· β±οΈ 21.11.2024):
pip install torchdiffeq -
Conda (π₯ 24K Β· β±οΈ 22.04.2025):
conda install -c conda-forge torchdiffeq
-
GitHub (π¨βπ» 9 Β· π 210 Β· π¦ 5.5K Β· π 84 - 36% open Β· β±οΈ 30.12.2024):
git clone https://github.com/google-research/torchsde -
PyPi (π₯ 4.6M / month Β· π¦ 37 Β· β±οΈ 26.09.2023):
pip install torchsde -
Conda (π₯ 46K Β· β±οΈ 22.04.2025):
conda install -c conda-forge torchsde
-
GitHub (π¨βπ» 34 Β· π 200 Β· π 420 - 6% open Β· β±οΈ 12.08.2025):
git clone https://github.com/rusty1s/pytorch_scatter -
PyPi (π₯ 82K / month Β· π¦ 150 Β· β±οΈ 06.10.2023):
pip install torch-scatter -
Conda (π₯ 1M Β· β±οΈ 03.10.2025):
conda install -c conda-forge pytorch_scatter
-
GitHub (π¨βπ» 48 Β· π 160 Β· π 300 - 10% open Β· β±οΈ 12.08.2025):
git clone https://github.com/rusty1s/pytorch_sparse -
PyPi (π₯ 63K / month Β· π¦ 120 Β· β±οΈ 06.10.2023):
pip install torch-sparse -
Conda (π₯ 940K Β· β±οΈ 03.10.2025):
conda install -c conda-forge pytorch_sparse
-
GitHub (π¨βπ» 9 Β· π 120 Β· π₯ 180 Β· π 33 - 12% open Β· β±οΈ 09.10.2025):
git clone https://github.com/BloodAxe/pytorch-toolbelt -
PyPi (π₯ 8.3K / month Β· π¦ 12 Β· β±οΈ 21.11.2024):
pip install pytorch_toolbelt
-
GitHub (π¨βπ» 3 Β· π 58 Β· π¦ 110 Β· β±οΈ 27.01.2025):
git clone https://github.com/facebookresearch/madgrad -
PyPi (π₯ 9.7K / month Β· π¦ 1 Β· β±οΈ 08.03.2022):
pip install madgrad
-
GitHub (π¨βπ» 6 Β· π 280 Β· π 72 - 47% open Β· β±οΈ 30.12.2024):
git clone https://github.com/szagoruyko/pytorchviz
- <b><a href="https://github.com/Cadene/pretrained-models.pytorch">pretrainedmodels</a></b> (π₯29 Β· β 9.1K Β· π) - 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> (π₯28 Β· β 8.2K Β· π) - 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> (π₯27 Β· β 1.7K Β· π) - 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> (π₯26 Β· β 3.1K Β· π) - 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> (π₯26 Β· β 2.9K Β· π) - 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> (π₯25 Β· β 1.6K Β· π) - 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> (π₯24 Β· β 4.1K Β· π) - 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> (π₯23 Β· β 1.6K Β· π) - 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> (π₯22 Β· β 14K Β· π) - 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> (π₯22 Β· β 2.1K Β· π) - 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> (π₯22 Β· β 1.7K Β· π) - pip install antialiased-cnns to improve stability and.. <code><a href="https://tldrlegal.com/search?q=CC%20BY-NC-SA%204.0">βοΈCC 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> (π₯21 Β· β 2.9K Β· π) - 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> (π₯21 Β· β 2.2K Β· π) - 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> (π₯21 Β· β 2K Β· π) - 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> (π₯21 Β· β 580) - A simplified framework and utilities for PyTorch. <code><a href="http://bit.ly/37RvQcA">βοΈLGPL-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> (π₯19 Β· β 1.2K Β· π) - 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> (π₯19 Β· β 1.1K Β· π) - 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> (π₯17 Β· β 1.5K Β· π) - 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> (π₯17 Β· β 400 Β· π) - 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> (π₯15 Β· β 320 Β· π) - 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> (π₯14 Β· β 1.2K Β· π) - 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> (π₯14 Β· β 810 Β· π) - 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>
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.
πΒ <b><a href="https://github.com/ml-tooling/best-of-python#database-clients">best-of-python - DB Clients</a></b> ( β 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> (π₯51 Β· 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 (π¨βπ» 1.8K Β· π 5.5K Β· π₯ 97K Β· π¦ 1.4M Β· π 11K - 15% open Β· β±οΈ 30.10.2025):
git clone https://github.com/scipy/scipy -
PyPi (π₯ 220M / month Β· π¦ 61K Β· β±οΈ 28.10.2025):
pip install scipy -
Conda (π₯ 70M Β· β±οΈ 29.10.2025):
conda install -c conda-forge scipy
-
GitHub (π¨βπ» 1.4K Β· π 4.8K Β· π₯ 570K Β· π¦ 290K Β· π 15K - 37% open Β· β±οΈ 30.10.2025):
git clone https://github.com/sympy/sympy -
PyPi (π₯ 73M / month Β· π¦ 4.6K Β· β±οΈ 27.04.2025):
pip install sympy -
Conda (π₯ 11M Β· β±οΈ 29.04.2025):
conda install -c conda-forge sympy
-
GitHub (π¨βπ» 570 Β· π 3.8K Β· π¦ 1M Β· π 5.7K - 23% open Β· β±οΈ 30.10.2025):
git clone https://github.com/streamlit/streamlit -
PyPi (π₯ 19M / month Β· π¦ 4.6K Β· β±οΈ 29.10.2025):
pip install streamlit
-
GitHub (π¨βπ» 700 Β· π 3.1K Β· π¦ 84K Β· π 6.1K - 6% open Β· β±οΈ 29.10.2025):
git clone https://github.com/gradio-app/gradio -
PyPi (π₯ 11M / month Β· π¦ 1.6K Β· β±οΈ 22.10.2025):
pip install gradio
-
GitHub (π¨βπ» 190 Β· π 4.2K Β· π¦ 1.1K Β· π 6.2K - 18% open Β· β±οΈ 30.10.2025):
git clone https://github.com/carla-simulator/carla -
PyPi (π₯ 18K / month Β· π¦ 16 Β· β±οΈ 14.09.2025):
pip install carla
-
GitHub (π¨βπ» 64 Β· π 910 Β· π¦ 14K Β· π 440 - 42% open Β· β±οΈ 27.10.2025):
git clone https://github.com/HIPS/autograd -
PyPi (π₯ 3.4M / month Β· π¦ 310 Β· β±οΈ 05.05.2025):
pip install autograd -
Conda (π₯ 680K Β· β±οΈ 05.05.2025):
conda install -c conda-forge autograd
-
GitHub (π¨βπ» 210 Β· π 700 Β· π₯ 100 Β· π¦ 1.9K Β· π 1.7K - 25% open Β· β±οΈ 30.10.2025):
git clone https://github.com/PennyLaneAI/PennyLane -
PyPi (π₯ 200K / month Β· π¦ 89 Β· β±οΈ 15.10.2025):
pip install pennylane -
Conda (π₯ 340K Β· β±οΈ 22.04.2025):
conda install -c conda-forge pennylane
-
GitHub (π¨βπ» 64 Β· π 1.4K Β· π¦ 5.5K Β· π 390 - 59% open Β· β±οΈ 29.04.2025):
git clone https://github.com/yzhao062/pyod -
PyPi (π₯ 840K / month Β· π¦ 130 Β· β±οΈ 29.04.2025):
pip install pyod -
Conda (π₯ 170K Β· β±οΈ 30.04.2025):
conda install -c conda-forge pyod
-
GitHub (π¨βπ» 82 Β· π 770 Β· π₯ 75 Β· π¦ 1.6K Β· π 1.9K - 32% open Β· β±οΈ 26.10.2025):
git clone https://github.com/simonw/datasette -
PyPi (π₯ 180K / month Β· π¦ 480 Β· β±οΈ 22.04.2025):
pip install datasette -
Conda (π₯ 73K Β· β±οΈ 22.04.2025):
conda install -c conda-forge datasette
-
GitHub (π¨βπ» 260 Β· π 1.9K Β· π¦ 650 Β· π 2.1K - 40% open Β· β±οΈ 27.10.2025):
git clone https://github.com/deepchem/deepchem -
PyPi (π₯ 54K / month Β· π¦ 24 Β· β±οΈ 27.10.2025):
pip install deepchem -
Conda (π₯ 120K Β· β±οΈ 22.04.2025):
conda install -c conda-forge deepchem
-
GitHub (π¨βπ» 75 Β· π 200 Β· π¦ 3.6K Β· π 930 - 15% open Β· β±οΈ 30.09.2025):
git clone https://github.com/serge-sans-paille/pythran -
PyPi (π₯ 500K / month Β· π¦ 28 Β· β±οΈ 23.05.2025):
pip install pythran -
Conda (π₯ 1.3M Β· β±οΈ 07.07.2025):
conda install -c conda-forge pythran
-
GitHub (π¨βπ» 55 Β· π 150 Β· π¦ 5.3K Β· π 650 - 0% open Β· β±οΈ 27.10.2025):
git clone https://github.com/wireservice/agate -
PyPi (π₯ 24M / month Β· π¦ 54 Β· β±οΈ 29.01.2025):
pip install agate -
Conda (π₯ 410K Β· β±οΈ 22.04.2025):
conda install -c conda-forge agate
-
GitHub (π¨βπ» 130 Β· π 590 Β· π¦ 800 Β· π 630 - 19% open Β· β±οΈ 05.10.2025):
git clone https://github.com/online-ml/river -
PyPi (π₯ 91K / month Β· π¦ 64 Β· β±οΈ 25.11.2024):
pip install river -
Conda (π₯ 130K Β· β±οΈ 22.04.2025):
conda install -c conda-forge river
-
GitHub (π¨βπ» 97 Β· π 500 Β· π¦ 7.6K Β· π 530 - 67% open Β· β±οΈ 11.10.2025):
git clone https://github.com/scikit-learn-contrib/hdbscan -
PyPi (π₯ 1.1M / month Β· π¦ 350 Β· β±οΈ 18.11.2024):
pip install hdbscan -
Conda (π₯ 2.8M Β· β±οΈ 09.09.2025):
conda install -c conda-forge hdbscan
-
GitHub (π¨βπ» 98 Β· π 820 Β· π₯ 42K Β· π¦ 200 Β· π 1.2K - 6% open Β· β±οΈ 27.10.2025):
git clone https://github.com/openvinotoolkit/anomalib -
PyPi (π₯ 200K / month Β· π¦ 7 Β· β±οΈ 09.10.2025):
pip install anomalib
-
GitHub (π¨βπ» 110 Β· π 170 Β· π¦ 980 Β· π 590 - 18% open Β· β±οΈ 21.10.2025):
git clone https://github.com/pyjanitor-devs/pyjanitor -
PyPi (π₯ 280K / month Β· π¦ 42 Β· β±οΈ 07.03.2025):
pip install pyjanitor -
Conda (π₯ 300K Β· β±οΈ 22.04.2025):
conda install -c conda-forge pyjanitor
-
GitHub (π¨βπ» 71 Β· π 830 Β· π¦ 310 Β· π 420 - 10% open Β· β±οΈ 26.09.2025):
git clone https://github.com/uber/causalml -
PyPi (π₯ 79K / month Β· π¦ 10 Β· β±οΈ 09.07.2025):
pip install causalml
-
GitHub (π¨βπ» 63 Β· π 200 Β· π¦ 22 Β· π 1.5K - 6% open Β· β±οΈ 30.10.2025):
git clone https://github.com/dstackai/dstack -
PyPi (π₯ 4.2K / month Β· β±οΈ 30.10.2025):
pip install dstack
-
GitHub (π¨βπ» 73 Β· π 290 Β· π¦ 1.1K Β· π 280 - 22% open Β· β±οΈ 05.05.2025):
git clone https://github.com/tensorly/tensorly -
PyPi (π₯ 130K / month Β· π¦ 99 Β· β±οΈ 12.11.2024):
pip install tensorly -
Conda (π₯ 380K Β· β±οΈ 22.04.2025):
conda install -c conda-forge tensorly
-
GitHub (π¨βπ» 52 Β· π 130 Β· π¦ 37 Β· π 370 - 27% open Β· β±οΈ 29.10.2025):
git clone https://github.com/transform-data/metricflow -
PyPi (π₯ 94K / month Β· π¦ 4 Β· β±οΈ 14.10.2025):
pip install metricflow
-
GitHub (π¨βπ» 18 Β· π 120 Β· π¦ 420 Β· π 210 - 7% open Β· β±οΈ 14.10.2025):
git clone https://github.com/sepandhaghighi/pycm -
PyPi (π₯ 190K / month Β· π¦ 28 Β· β±οΈ 15.10.2025):
pip install pycm
-
GitHub (π¨βπ» 16 Β· π 190 Β· π¦ 770 Β· β±οΈ 04.08.2025):
git clone https://github.com/MaxHalford/prince -
PyPi (π₯ 230K / month Β· π¦ 23 Β· β±οΈ 04.08.2025):
pip install prince -
Conda (π₯ 28K Β· β±οΈ 22.04.2025):
conda install -c conda-forge prince-factor-analysis
-
GitHub (π¨βπ» 82 Β· π 830 Β· π¦ 230 Β· π 250 - 50% open Β· β±οΈ 26.09.2025):
git clone https://github.com/google/trax -
PyPi (π₯ 4.3K / month Β· π¦ 1 Β· β±οΈ 26.10.2021):
pip install trax
-
GitHub (π¨βπ» 17 Β· π 360 Β· π¦ 260 Β· π 410 - 10% open Β· β±οΈ 12.10.2025):
git clone https://github.com/Adapter-Hub/adapter-transformers -
PyPi (π₯ 4.9K / month Β· π¦ 12 Β· β±οΈ 07.07.2024):
pip install adapter-transformers
-
GitHub (π¨βπ» 42 Β· π 310 Β· π¦ 180 Β· π 80 - 30% open Β· β±οΈ 27.10.2025):
git clone https://github.com/facebookresearch/AugLy -
PyPi (π₯ 13K / month Β· π¦ 4 Β· β±οΈ 05.12.2023):
pip install augly
-
GitHub (π¨βπ» 87 Β· π 310 Β· π₯ 60 Β· π¦ 140 Β· π 840 - 13% open Β· β±οΈ 11.03.2025):
git clone https://github.com/ContinualAI/avalanche -
PyPi (π₯ 3.2K / month Β· π¦ 3 Β· β±οΈ 29.10.2024):
pip install avalanche-lib
-
GitHub (π¨βπ» 12 Β· π 300 Β· π¦ 730 Β· π 220 - 11% open Β· β±οΈ 23.07.2025):
git clone https://github.com/trevorstephens/gplearn -
PyPi (π₯ 20K / month Β· π¦ 19 Β· β±οΈ 03.05.2022):
pip install gplearn -
Conda (π₯ 11K Β· β±οΈ 22.04.2025):
conda install -c conda-forge gplearn
-
GitHub (π¨βπ» 51 Β· π 600 Β· π¦ 220 Β· π 320 - 6% open Β· β±οΈ 25.11.2024):
git clone https://github.com/tableau/TabPy -
PyPi (π₯ 7.1K / month Β· π¦ 2 Β· β±οΈ 25.11.2024):
pip install tabpy -
Conda (π₯ 5.8K Β· β±οΈ 22.04.2025):
conda install -c anaconda tabpy-client
-
GitHub (π¨βπ» 16 Β· π 72 Β· π¦ 5.6K Β· π 23 - 47% open Β· β±οΈ 04.09.2025):
git clone https://github.com/minrk/findspark -
PyPi (π₯ 2.6M / month Β· π¦ 100 Β· β±οΈ 11.02.2022):
pip install findspark -
Conda (π₯ 1M Β· β±οΈ 22.04.2025):
conda install -c conda-forge findspark
-
GitHub (π¨βπ» 1 Β· π 82 Β· π¦ 570 Β· β±οΈ 28.09.2025):
git clone https://github.com/vecxoz/vecstack -
PyPi (π₯ 1.8K / month Β· π¦ 5 Β· β±οΈ 28.09.2025):
pip install vecstack -
Conda (π₯ 3K Β· β±οΈ 22.04.2025):
conda install -c conda-forge vecstack
-
GitHub (π¨βπ» 69 Β· π 240 Β· π₯ 130K Β· π 560 - 26% open Β· β±οΈ 14.08.2025):
git clone https://github.com/Project-MONAI/MONAILabel -
PyPi (π₯ 200 / month Β· β±οΈ 01.10.2023):
pip install monailabel-weekly
-
GitHub (π¨βπ» 4 Β· π 49 Β· π₯ 33 Β· π¦ 200 Β· π 34 - 38% open Β· β±οΈ 09.06.2025):
git clone https://github.com/jmschrei/apricot -
PyPi (π₯ 13K / month Β· π¦ 16 Β· β±οΈ 18.02.2021):
pip install apricot-select
-
GitHub (π¨βπ» 28 Β· π 70 Β· π¦ 6 Β· π 140 - 8% open Β· β±οΈ 14.10.2025):
git clone https://github.com/pykale/pykale -
PyPi (π₯ 72 / month Β· β±οΈ 12.04.2022):
pip install pykale
-
GitHub (π¨βπ» 3 Β· π 49 Β· π¦ 560 Β· π 15 - 80% open Β· β±οΈ 24.03.2025):
git clone https://github.com/yzhao062/SUOD -
PyPi (π₯ 13K / month Β· π¦ 9 Β· β±οΈ 24.03.2025):
pip install suod
-
GitHub (π¨βπ» 19 Β· π 110 Β· π 130 - 39% open Β· β±οΈ 09.09.2025):
git clone https://github.com/infer-actively/pymdp -
PyPi (π₯ 1.1K / month Β· β±οΈ 08.12.2022):
pip install inferactively-pymdp
- <b><a href="https://github.com/inducer/pyopencl">pyopencl</a></b> (π₯31 Β· β 1.1K) - OpenCL integration for Python, plus shiny features. <code>βUnlicensed</code>
- <b><a href="https://github.com/google-deepmind/pysc2">pysc2</a></b> (π₯30 Β· β 8.2K Β· π) - StarCraft II Learning Environment. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/modAL-python/modAL">modAL</a></b> (π₯30 Β· β 2.3K Β· π) - A modular active learning framework 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>
- <b><a href="https://github.com/datalad/datalad">datalad</a></b> (π₯30 Β· β 620 Β· π) - Keep code, data, containers under control with git and git-.. <code>βUnlicensed</code>
- <b><a href="https://github.com/cleanlab/cleanlab">cleanlab</a></b> (π₯29 Β· β 11K) - Cleanlabs open-source library is the standard data-centric AI.. <code><a href="http://bit.ly/3pwmjO5">βοΈAGPL-3.0</a></code>
- <b><a href="https://github.com/SeldonIO/alibi-detect">alibi-detect</a></b> (π₯29 Β· β 2.4K) - Algorithms for outlier, adversarial and drift detection. <code><a href="https://tldrlegal.com/search?q=Intel">βοΈIntel</a></code>
- <b><a href="https://github.com/JustGlowing/minisom">minisom</a></b> (π₯28 Β· β 1.6K) - MiniSom is a minimalistic implementation of the Self Organizing.. <code><a href="https://tldrlegal.com/search?q=CC-BY-3.0">βοΈCC-BY-3.0</a></code>
- <b><a href="https://github.com/ljvmiranda921/pyswarms">PySwarms</a></b> (π₯28 Β· β 1.4K Β· π) - 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> (π₯28 Β· β 1.3K Β· π) - 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> (π₯28 Β· β 1.2K Β· π) - pyclustering is a Python, C++ data mining library. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/explosion/cython-blis">Cython BLIS</a></b> (π₯28 Β· β 230) - Fast matrix-multiplication as a self-contained Python library no.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/solegalli/feature_engine">Feature Engine</a></b> (π₯26 Β· β 2.1K Β· π) - Feature engineering package with sklearn like functionality. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/scikit-learn-contrib/metric-learn">metric-learn</a></b> (π₯26 Β· β 1.4K Β· π) - 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> (π₯25 Β· β 22K) - Chat with your database or your datalake (SQL, CSV, parquet)... <code>βUnlicensed</code>
- <b><a href="https://github.com/mars-project/mars">Mars</a></b> (π₯24 Β· β 2.7K Β· π) - Mars is a tensor-based unified framework for large-scale data.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/astroML/astroML">AstroML</a></b> (π₯24 Β· β 1.1K Β· π) - Machine learning, statistics, and data mining for astronomy.. <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/PaddlePaddle/PaddleHub">PaddleHub</a></b> (π₯22 Β· β 13K Β· π) - 400+ AI Models: Rich, high-quality AI models, including.. <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/ml-tooling/opyrator">opyrator</a></b> (π₯22 Β· β 3.1K Β· π) - Turns your machine learning code into microservices with web API,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/flennerhag/mlens">mlens</a></b> (π₯22 Β· β 860 Β· π) - ML-Ensemble high performance ensemble learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/BioPandas/biopandas">BioPandas</a></b> (π₯22 Β· β 740 Β· π) - Working with molecular structures in pandas DataFrames. <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>
- <b><a href="https://github.com/clementchadebec/benchmark_VAE">benchmark_VAE</a></b> (π₯21 Β· β 2K Β· π) - Unifying Variational Autoencoder (VAE).. <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/eltonlaw/impyute">impyute</a></b> (π₯21 Β· β 360 Β· π) - Data imputations library to preprocess datasets with missing data. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/airbnb/streamalert">StreamAlert</a></b> (π₯20 Β· β 2.9K Β· π) - StreamAlert is a serverless, realtime data analysis.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/kLabUM/rrcf">rrcf</a></b> (π₯20 Β· β 520 Β· π) - Implementation of the Robust Random Cut Forest algorithm for anomaly.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/EpistasisLab/scikit-rebate">scikit-rebate</a></b> (π₯20 Β· β 420 Β· π) - A scikit-learn-compatible Python implementation 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/alegonz/baikal">baikal</a></b> (π₯18 Β· β 590 Β· π) - A graph-based functional API for building complex scikit-learn.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/pandas-ml/pandas-ml">pandas-ml</a></b> (π₯16 Β· β 320 Β· π) - pandas, scikit-learn, xgboost and seaborn integration. <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>
- <b><a href="https://github.com/SforAiDl/KD_Lib">KD-Lib</a></b> (π₯15 Β· β 650 Β· π) - A Pytorch Knowledge Distillation library for benchmarking 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>
- <b><a href="https://github.com/facebookresearch/NeuralCompression">NeuralCompression</a></b> (π₯14 Β· β 580 Β· π) - A collection of tools for neural compression enthusiasts. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/jrieke/traingenerator">traingenerator</a></b> (π₯13 Β· β 1.4K Β· π) - A web app to generate template code for machine learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/Palashio/nylon">nylon</a></b> (π₯12 Β· β 82 Β· π) - An intelligent, flexible grammar of machine learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
Related Resources
- Papers With Code: Discover ML papers, code, and evaluation tables.
- Sotabench: Discover & compare open-source ML models.
- Google Dataset Search: Dataset search engine by Google.
- Dataset List: List of the biggest ML datasets from across the web.
- Awesome Public Datasets: A topic-centric list of open datasets.
- Best-of lists: Discover other best-of lists with awesome open-source projects on all kinds of topics.
- best-of-python-dev: A ranked list of awesome python developer tools and libraries.
- best-of-web-python: A ranked list of awesome python libraries for web development.
Contribution
Contributions are encouraged and always welcome! If you like to add or update projects, choose one of the following ways:
- Open an issue by selecting one of the provided categories from the issue page and fill in the requested information.
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If you like to contribute to or share suggestions regarding the project metadata collection or markdown generation, please refer to the best-of-generator repository. If you like to create your own best-of list, we recommend to follow this guide.
For more information on how to add or update projects, please read the contribution guidelines. By participating in this project, you agree to abide by its Code of Conduct.