menu
{ "item_title" : "Machine Unlearning", "item_author" : [" Bitan Misra", "Sayan Chakraborty", "Nilanjan Dey "], "item_description" : "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.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/1/04/129/531/1041295316_b.jpg", "price_data" : { "retail_price" : "115.99", "online_price" : "115.99", "our_price" : "115.99", "club_price" : "115.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Machine Unlearning|Bitan Misra

Machine Unlearning : Principles, Methods, and Evolving Frontiers

PRE-ORDER NOW:
local_shippingShip to Me
Preorder. This item will be available on October 13, 2026 .
FREE Shipping for Club Members help

Overview

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.

This item is Non-Returnable

Details

  • ISBN-13: 9781041295310
  • ISBN-10: 1041295316
  • Publisher: CRC Press
  • Publish Date: October 2026
  • Page Count: 106

Related Categories

You May Also Like...

    1

BAM Customer Reviews