Expanded chapter on intrinsic explainable models for deeper understanding and new examples
Updated section on model-agnostic XAI methods and adversarial machine learning for better grasp of explanation differences
New chapter on generative models and large language models, exploring their role in XAI and transformer explanations
Interactive visual approach to XAI concepts for enhanced accessibility
Code reviews and optimized examples for current best practices in adversarial machine learning
Summarized by Shop
This comprehensive book on Explainable Artificial Intelligence has been updated and expanded to reflect the latest advancements in the field of XAI, enriching the existing literature with new research, case studies, and practical techniques. The Second Edition expands on its predecessor by addressing advancements in AI, including large l