Table of Contents
- Explaining Artificial Intelligence with Python
- White Box XAI for AI Bias and Ethics
- Explaining Machine Learning with Facets
- Microsoft Azure Machine Learning Model Interpretability with SHAP
- Building an Explainable AI Solution from Scratch
- AI Fairness with Google's What-If Tool (WIT)
- A Python Client for Explainable AI Chatbots
- Local Interpretable Model-Agnostic Explanations (LIME)
- The Counterfactual Explanations Method
- Contrastive XAI
- Anchors XAI
- Cognitive XAI

