interpretation

Shapash: Making ML Models Understandable by Everyone (link)
Explainable AI Cheat Sheet (link)
Explain Your Model with the SHAP Values (link)
SHAP Doc (link)
SHAP git (link)
Interpretable Machine Learning - Christoph Molnar - Book (link)
Guide to Interpretable Machine Learning (link)
Intuitive Interpretation of Random Forest (link)
Increasing Tree Classifier interpretability with SHAP (link)
Random Forest Interpretation (link)
treeinterpreter - Interpreting Tree-Based Model’s Prediction of Individual Sample (link)
Why is that house so expensive? Ask a Random Forest! (link)
Interpretable Machine Learning with Python (link)
ELI5 Doc (link)
Demystifying Model Interpretation using ELI5 (link)
How to Use eli5 to Understand sklearn Models, their Performance, and their Predictions (link)