ISBN: 9781041295310 - machine unlearning: principles, methods, and evolving frontiers (9 resultados)

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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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EUR 135,90
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Condición: New.

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Librería: moluna, Greven, Alemaniamoluna
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EUR 121,49
Envío por EUR 48,99Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New. Bitan Misra is currently working as an assistant professor in the Department of Computer Science and Engineering, Techno International New Town, Kolkata, India. She received a B. Tech. and M. Tech. dual degree in electronics and telecommunication .

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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 163,20
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Buch. Condición: Neu. Neuware - 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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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
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EUR 104,28
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Hardcover. Condición: new. Hardcover. 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. This book explores machine unlearning, a vital AI field for selectively removing learned data from models. Covering advanced techniques, real-world case studies, and ethical considerations like GDPR compliance, it equips readers to implement responsible AI systems while addressing data privacy and societal challenges. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US
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EUR 134,87
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HRD. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

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Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
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EUR 130,62
Envío por EUR 11,16Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
HRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

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Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
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EUR 101,94
Envío por EUR 44,13Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponible
Hardcover. Condición: new. Hardcover. 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. This book explores machine unlearning, a vital AI field for selectively removing learned data from models. Covering advanced techniques, real-world case studies, and ethical considerations like GDPR compliance, it equips readers to implement responsible AI systems while addressing data privacy and societal challenges. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

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Librería: THE SAINT BOOKSTORE, Southport, Reino UnidoTHE SAINT BOOKSTORE
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EUR 152,90
Envío por EUR 19,09Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

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Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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EUR 140,10
Envío por EUR 32,98Se envía de Australia a Estados Unidos de AmericaCantidad disponible: 1 disponible
Hardcover. Condición: new. Hardcover. 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. This book explores machine unlearning, a vital AI field for selectively removing learned data from models. Covering advanced techniques, real-world case studies, and ethical considerations like GDPR compliance, it equips readers to implement responsible AI systems while addressing data privacy and societal challenges. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…