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7 repositories · updated 2026-11-06
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1shap / shapA game theoretic approach to explain the output of any machine learning model.Jupyter NotebookMIT · PermissiveInsufficient rank history25,850
2EthicalML / awesome-production-machine-learningA curated list of awesome open source libraries to deploy, monitor, version and scale your machine learningMIT · PermissiveInsufficient rank history21,075
3jacobgil / pytorch-grad-camAdvanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.PythonMIT · PermissiveInsufficient rank history13,009
4interpretml / interpretFit interpretable models. Explain blackbox machine learning.C++MIT · PermissiveInsufficient rank history6,976
5meta-pytorch / captumModel interpretability and understanding for PyTorchPythonBSD-3-Clause · PermissiveInsufficient rank history5,719
6jphall663 / awesome-machine-learning-interpretabilityA curated list of awesome responsible machine learning resources.CC0-1.0 · PermissiveInsufficient rank history4,084
7csinva / imodelsInterpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).Jupyter NotebookMIT · PermissiveInsufficient rank history1,630
