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Book synopsis

This book explores one of the most critical and emerging fields in artificial intelligence, machine unlearning. As data privacy concerns grow and regulations like GDPR 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. It is for researchers, AI practitioners, and professionals seeking to understand and implement machine unlearning for data privacy, ethical AI design, and regulatory compliance.

Book details

Book category Books in English Technology, engineering, agriculture Electronics & communications engineering Electronics engineering

• Full title: Machine Unlearning
• Author: Nilanjan Dey, Sayan Chakraborty
• Language: English
• Binding: Hardback
• Number of pages: 136
• EAN: 9781041295310
• ISBN: 1041295316
• ID: 52136161
• Publisher: Taylor & Francis Ltd
• Dimensions: 234 × 156 mm
• Date of publishing: 10. September 2026

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