shapash by MAIF

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

updated at Nov. 15, 2024, 9:09 p.m.

38 +0

2,738 +1

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xai by EthicalML

XAI - An eXplainability toolbox for machine learning

updated at Nov. 16, 2024, 8:11 a.m.

43 +0

1,125 +6

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shap by shap

A game theoretic approach to explain the output of any machine learning model.

updated at Nov. 16, 2024, 6:20 p.m.

245 +1

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what-if-tool by PAIR-code

Source code/webpage/demos for the What-If Tool

updated at Nov. 16, 2024, 8:25 p.m.

29 +0

918 +3

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