Course content
- Introduction to XAI
- Demonstration of By Design Interpretable Models: Glass
- Box
- LIME (Local Interpretable Model Agnostic Explanations)
- SHAP (SHapIey Additive exPIanations)
- Counterfactual Explanations
- Google’s What-if Tool (WIT) for A1 fairness and Counterfactuals
- Layer-wise Relevance Propagation (LRP)
- Contrastive Explanations Method (CEM)
- Useful Resources for XAI
- Final Quiz
- Surprise on Completion of Course
- Other resources from the Instructor
- Acknowledgement