Deep learning: foundations and concepts / by Christopher M. Bishop and Hugh Bishop

By:

Bishop, Christopher M [Author]

Contributor(s):

Bishop, Hugh [Joint author]

Language: English Publication details: Switzerland : Springer Nature, 2024Description: v, 649 p. : ill. ; 28 cmISBN:

9783031454677 (hbk.)

Subject(s):

Deep Learning

DDC classification:

006.31 BIS/D

Summary: This book offers a comprehensive introduction to the central ideas that underpin deep learning. It is intended both for newcomers to machine learning and for those already experienced in the field. Covering key concepts relating to contemporary architectures and techniques, this essential book equips readers with a robust foundation for potential future specialization. The field of deep learning is undergoing rapid evolution, and therefore this book focusses on ideas that are likely to endure the test of time.

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Holdings
Cover image	Item type	Current library	Home library	Collection	Shelving location	Call number	Materials specified	Vol info	URL	Copy number	Status	Notes	Date due	Barcode	Item holds	Item hold queue priority	Course reserves
	Technical Reference Book	Central Library, IIT Bhubaneswar	Central Library, IIT Bhubaneswar	SMS		006.31 BIS/D (Browse shelf(Opens below))					Checked out		16/10/2025	11144

Total holds: 1

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Previous	006.3 VIS/D Distributed intellegence : building an autonomous tech ecosystem with AI, blockchain, IoT and green energy /	006.31 ALP/I Introduction to machine learning /	006.31 BAN/H Hands on tinyML : harness the power of machine learning on the edge devices /	006.31 BIS/D Deep learning: foundations and concepts /	006.31 CHO/D Deep learning with Python /	006.31 CHO/D Deep learning with Python /	006.31 CHO/D Deep learning with Python /	Next

Includes bibliographical references and index.

This book offers a comprehensive introduction to the central ideas that underpin deep learning. It is intended both for newcomers to machine learning and for those already experienced in the field. Covering key concepts relating to contemporary architectures and techniques, this essential book equips readers with a robust foundation for potential future specialization. The field of deep learning is undergoing rapid evolution, and therefore this book focusses on ideas that are likely to endure the test of time.

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