000			03587cam a2200505M 4500
001			9781003466581
003			FlBoTFG
005			20251030122251.0
006			m o d
007			cr |n|||||||||
008			240725s2024 xx o 0|| 0 eng d
040			_aOCoLC-P _beng _cOCoLC-P
020			_a9781040115350 _q(electronic bk.)
020			_a1040115357 _q(electronic bk.)
020			_a9781003466581 _q(electronic bk.)
020			_a1003466583 _q(electronic bk.)
020			_a9781040115336 _q(electronic bk. : PDF)
020			_a1040115330 _q(electronic bk. : PDF)
020			_z1032724323
020			_z9781032724324
024	7		_a10.1201/9781003466581 _2doi
035			_a(OCoLC)1449623977
035			_a(OCoLC-P)1449623977
050		4	_aQ325.5
072		7	_aCOM _x094000 _2bisacsh
072		7	_aCOM _x004000 _2bisacsh
072		7	_aCOM _x053000 _2bisacsh
072		7	_aUY _2bicssc
245	0	0	_aFEDERATED LEARNING _h[electronic resource] : _bunlocking the power of collaborative intelligence.
260			_a[S.l.] : _bCRC PRESS, _c2024.
300			_a1 online resource
520			_aFederated Learning:Unlocking the Power of Collaborative Intelligence is a definitive guide to the transformative potential of federated learning. This book delves into federated learning principles, techniques, and applications, and offers practical insights and real-world case studies to showcase its capabilities and benefits. The book begins with a survey of the fundamentals of federated learning and its significance in the era of privacy concerns and data decentralization. Through clear explanations and illustrative examples, the book presents various federated learning frameworks, architectures, and communication protocols. Privacy-preserving mechanisms are also explored,such asdifferential privacy and secure aggregation, offering the practical knowledge needed to address privacy challenges in federated learning systems. This book concludes by highlighting the challenges and emerging trends in federated learning, emphasizing the importance of trust, fairness, and accountability, and provides insights into scalability and efficiency considerations. With detailed case studies and step-by-step implementation guides, this book shows how to build and deploy federated learning systems in real-world scenarios - such as in healthcare, finance, Internet of things (IoT), and edge computing. Whether you are a researcher, a data scientist, or a professional exploring the potential of federated learning, this book will empower you with the knowledge and practical tools needed to unlock the power of federated learning and harness the collaborative intelligence of distributed systems. Key Features: Provides a comprehensive guide on tools and techniques of federated learning Highlights many practical real-world examples Includes easy-to-understand explanations
588			_aOCLC-licensed vendor bibliographic record.
650		0	_aMachine learning. _955059
650		0	_aFederated learning (Machine learning) _994903
650		7	_aCOMPUTERS / Artificial Intelligence _2bisacsh
650		7	_aCOMPUTERS / Security / General _2bisacsh _964313
700	1		_aUddin, M. Irfan, _d1982- _994904
700	1		_aMashwani, Wali Khan, _d1972- _994905
856	4	0	_3Taylor & Francis _uhttps://www.taylorfrancis.com/books/9781003466581
856	4	2	_3OCLC metadata license agreement _uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
942			_cE-Books
999			_c67921 _d67921