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About Explainable AI with Python, 2E
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 language models and multimodal systems that integrate text, visual, auditory, and sensor data. It emphasizes making complex systems interpretable without sacrificing performance and provides an enhanced focus on additive models for improved interpretability. Balancing technical rigor with accessibility, the book combines theory and practical application to equip readers with the skills needed to apply explainable AI (XAI) methods effectively in real-world contexts. Through detailed theoretical explanations and hands-on Python examples, readers are invited to explore diverse methodologies employed in making AI systems explainable–be it through model-agnostic approaches that treat the AI as a black box or intrinsic methods that weave interpretability into the model’s architecture.
Detailed Information
| Author: | Antonio Di Cecco |
|---|---|
| Pages: | 331 |
| Language: | English |
| File Size: | 20 |
| Format: | |
| Price: | FREE |
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