Development and Analysis of Deep Learning Architectures (Hardcover, 1st ed. 2020)

This book offers a timely reflection on the remarkable range of algorithms and applications that have made the area of deep learning so attractive and heavily researched today. Introducing the diversity of learning mechanisms in the environment of big data, and presenting authoritative studies in fields such as sensor design, health care, autonomous driving, industrial control and wireless communication, it enables readers to gain a practical understanding of design. The book also discusses systematic design procedures, optimization techniques, and validation processes.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Studies in Computational Intelligence, 867
Release date:	November 2019
First published:	2020
Editors:	Witold Pedrycz • Shyi-Ming Chen
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	292
Edition:	1st ed. 2020
ISBN-13:	978-3-03-031763-8
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-03-031763-3
Barcode:	9783030317638

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