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Deep learning = algorithms and appli...

Pedrycz, Witold.

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Deep learning = algorithms and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Deep learning/ edited by Witold Pedrycz, Shyi-Ming Chen.
Reminder of title:	algorithms and applications /
other author:	Pedrycz, Witold.
Published:	Cham :Springer International Publishing : : 2020.,
Description:	xii, 360 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Preface -- Chapter 1. Activation Functions -- Chapter 2. Adversarial Examples in Deep Neural Networks: An Overview -- Chapter 3. Representation Learning in Power Time Series Forecasting, etc.
Contained By:	Springer eBooks
Subject:	Machine learning. -
Online resource:	https://doi.org/10.1007/978-3-030-31760-7
ISBN:	9783030317607

Deep learning = algorithms and applications /
Deep learningalgorithms and applications /[electronic resource] :edited by Witold Pedrycz, Shyi-Ming Chen. - Cham :Springer International Publishing :2020. - xii, 360 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.8651860-949X ;. - Studies in computational intelligence ;v.865..

Preface -- Chapter 1. Activation Functions -- Chapter 2. Adversarial Examples in Deep Neural Networks: An Overview -- Chapter 3. Representation Learning in Power Time Series Forecasting, etc.

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.

ISBN: 9783030317607

Standard No.: 10.1007/978-3-030-31760-7doiSubjects--Topical Terms:

533906
Machine learning.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

Deep learning = algorithms and applications /
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245 0 0 $a Deep learning $h [electronic resource] : $b algorithms and applications / $c edited by Witold Pedrycz, Shyi-Ming Chen.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a xii, 360 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-949X ; $v v.865
505 0 $a Preface -- Chapter 1. Activation Functions -- Chapter 2. Adversarial Examples in Deep Neural Networks: An Overview -- Chapter 3. Representation Learning in Power Time Series Forecasting, etc.
520 $a 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.
650 0 $a Machine learning. $3 533906
650 0 $a Computer algorithms. $3 523872
650 1 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Artificial Intelligence. $3 769149
700 1 $a Pedrycz, Witold. $3 899642
700 1 $a Chen, Shyi-Ming. $3 1067501
710 2 $a SpringerLink (Online service) $3 836513
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830 0 $a Studies in computational intelligence ; $v v.865. $3 3444521
856 4 0 $u https://doi.org/10.1007/978-3-030-31760-7
950 $a Intelligent Technologies and Robotics (Springer-42732)