Book Content
chapters • 7h16m total length
1. Understanding Deep Learning Anomaly Detection
2. Understanding Explainable AI
3. Natural Language Processing Anomaly Explainability
4. Time Series Anomaly Explainability
5. Computer Vision Anomaly Explainability
6. Differentiating Intrinsic versus Post Hoc Explainability
7. Backpropagation Versus Perturbation Explainability
8. Model-Agnostic versus Model-Specific Explainability
9. Explainability Evaluation Schemes
