Deep Learning: Algorithms and Applications (Paperback, 1st ed. 2020)

This book presents a wealth of deep-learning algorithms and demonstrates their design process. It also highlights the need for a prudent alignment with the essential characteristics of the nature of learning encountered in the practical problems being tackled. Intended for readers interested in acquiring practical knowledge of analysis, design, and deployment of deep learning solutions to real-world problems, it covers a wide range of the paradigm's algorithms and their applications in diverse areas including imaging, seismic tomography, smart grids, surveillance and security, and health care, among others. Featuring systematic and comprehensive discussions on the development processes, their evaluation, and relevance, the book offers insights into fundamental design strategies for algorithms of deep learning.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Studies in Computational Intelligence, 865
Release date:	November 2020
First published:	2020
Editors:	Witold Pedrycz • Shyi-Ming Chen
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	360
Edition:	1st ed. 2020
ISBN-13:	978-3-03-031762-1
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-03-031762-5
Barcode:	9783030317621

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