shapash by MAIF

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

updated at April 26, 2024, 7:52 a.m.

37 +0

2,644 +4

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xai by EthicalML

XAI - An eXplainability toolbox for machine learning

updated at April 26, 2024, 6:55 p.m.

44 +0

1,062 +5

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what-if-tool by PAIR-code

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

updated at April 28, 2024, 9:51 a.m.

29 +0

884 +4

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shap by shap

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

updated at April 28, 2024, 3:23 p.m.

240 -1

21,638 +59

3,167 +3