Interpretable Machine Learning
Explainable AI and Fair Machine Learning (with R and Python)
About
Introduction
Interpretable Machine Learning
Feature Importance
PDP + ICE + ALE
Feature Interaction
Lime + Surrogates
Shapley Values and SHAP
Text & image data
Algorithmic Fairness
Outlook: Further interpretability methods
Own project
Appendix
Interpretable Machine Learning
Link to the slides