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Book Synopsis

Chapter 1 The Landscape.- Chapter 2 "Explainable AI: needs, opportunities and challenges".- Chapter 3 Intrinsic Explainable Models.- Chapter 4 Model-agnostic methods for XAI.- Chapter 5 Explaining Deep Learning Models.- Chapter 6 Additive Models for Interpretability.- Chapter 7 Adversarial Machine Learning and Explainability.-Chapter 8 Explainability of Language Models (XAI and LLM).- Chapter 9 Making science with Machine Learning and XAI.- Chapter 10 AGI, LLM, XAI.- Chapter 11 "A proposal for a sustainable model of Explainable AI.

Explainable AI with Python

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    A Paperback by Antonio Di Cecco

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      Publisher: Springer
      Publication Date: Publication Date: 9/20/2025
      ISBN13: 9783031922282, 978-3031922282
      ISBN10: 303192228X
      Also in:
      Computing Artificial intelligence (AI)

      Description

      Book Synopsis

      Chapter 1 The Landscape.- Chapter 2 "Explainable AI: needs, opportunities and challenges".- Chapter 3 Intrinsic Explainable Models.- Chapter 4 Model-agnostic methods for XAI.- Chapter 5 Explaining Deep Learning Models.- Chapter 6 Additive Models for Interpretability.- Chapter 7 Adversarial Machine Learning and Explainability.-Chapter 8 Explainability of Language Models (XAI and LLM).- Chapter 9 Making science with Machine Learning and XAI.- Chapter 10 AGI, LLM, XAI.- Chapter 11 "A proposal for a sustainable model of Explainable AI.

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