Explainable Artificial Intelligence: An Introduction to Interpretable Machine Learning
This book is a great guide to anyonewho is new to the field of XAI or is already familiar with the field and is willing to expand their knowledge. A comprehensive review of the state-of-the-art Explainable AI methods starting from visualization, interpretable methods, local and global explanations,...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Cham
Springer International Publishing
2021, 2021
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| Edition: | 1st ed. 2021 |
| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- 1. Introduction to Interpretability and Explainability
- 2. Pre-Model Interpretability and Explainability
- 3. Model Visualization Techniques and Traditional Interpretable Algorithms
- 4. Model Interpretability: Advances in Interpretable Machine Learning
- 5. Post-hoc Interpretability and Explanations
- 6. Explainable Deep Learning
- 7. Explainability in Time Series Forecasting, Natural Language Processing, and Computer Vision
- 8. XAI: Challenges and Future