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

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Da: California Books, Miami, FL, U.S.A.California Books
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EUR 136,43
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Condizione: New.

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Da: moluna, Greven, Germaniamoluna
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EUR 121,49
EUR 48,99 spedizioneSpedito da Germania a U.S.A.Quantità: Più di 20 disponibili
Condizione: 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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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 163,20
EUR 35,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Buch. Condizione: 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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Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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EUR 104,68
Spedizione gratuitaSpedito in U.S.A.Quantità: 1 disponibile
Hardcover. Condizione: 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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Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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EUR 135,40
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HRD. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

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Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
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EUR 130,81
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HRD. Condizione: 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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Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 102,09
EUR 44,19 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibile
Hardcover. Condizione: 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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Da: THE SAINT BOOKSTORE, Southport, Regno UnitoTHE SAINT BOOKSTORE
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EUR 153,12
EUR 19,12 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

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Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 140,45
EUR 33,11 spedizioneSpedito da Australia a U.S.A.Quantità: 1 disponibile
Hardcover. Condizione: 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.…