Machine Unlearning - Principles, Methods, and Evolving Frontiers
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Last checked: Sep. 30th '26
Date uploaded: Sep. 30th '26
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INFO HASH: 22C75BC03AD4F1BCA768A24B9D126B55B79F7427
Machine Unlearning: Principles, Methods, and Evolving Frontiers

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English | 2026 | ISBN: 1041295316 | 118 pages | True PDF,EPUB | 5.37 MB
This book explores one of the most critical and emerging fields in artificial intelligence (AI): machine unlearning. As data privacy concerns grow and regulations like GDPR (General Data Protection Regulation) demand compliance, this book provides a comprehensive guide to selectively removing learned information from machine learning models without sacrificing performance or requiring complete retraining. Covering foundational principles, advanced algorithms, benchmarking tools, and real-world case studies in healthcare, finance, and social media, the book bridges the gap between theory and practice. It also addresses ethical, legal, and societal implications, offering insights into creating trustworthy AI systems. This book is an essential resource for understanding and implementing machine unlearning in the era of responsible AI.
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