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Principles of artificial neural netw...

Graupe, Daniel.

Principles of artificial neural networks = basic designs to deep learning /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Principles of artificial neural networks/ Daniel Graupe.
Reminder of title:	basic designs to deep learning /
Author:	Graupe, Daniel.
Published:	Singapore :World Scientific Publishing, : c2019.,
Description:	1 online resource (440 p.) :ill. :
Subject:	Neural networks (Computer science) -
Online resource:	https://www.worldscientific.com/worldscibooks/10.1142/11306#t=toc
ISBN:	9789811201233

Principles of artificial neural networks = basic designs to deep learning /
Graupe, Daniel.

Principles of artificial neural networksbasic designs to deep learning /[electronic resource] :Daniel Graupe. - 4th ed. - Singapore :World Scientific Publishing,c2019. - 1 online resource (440 p.) :ill. - Advanced series in circuits and systems ;vol. 8. - Advanced series in circuits and systems ;v. 8.

Includes bibliographical references (p. 401-414) and indexes.

"The field of Artificial Neural Networks is the fastest growing field in Information Technology and specifically, in Artificial Intelligence and Machine Learning. This must-have compendium presents the theory and case studies of artificial neural networks. The volume, with 4 new chapters, updates the earlier edition by highlighting recent developments in Deep-Learning Neural Networks, which are the recent leading approaches to neural networks. Uniquely, the book also includes case studies of applications of neural networks — demonstrating how such case studies are designed, executed and how their results are obtained. The title is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers in medicine, finance and data mining."--

ISBN: 9789811201233Subjects--Topical Terms:

528588
Neural networks (Computer science)

LC Class. No.: QA76.87 / .G77 2019

Dewey Class. No.: 006.3/2

Principles of artificial neural networks = basic designs to deep learning /
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050 0 4 $a QA76.87 $b .G77 2019
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100 1 $a Graupe, Daniel. $3 568238
245 1 0 $a Principles of artificial neural networks $h [electronic resource] : $b basic designs to deep learning / $c Daniel Graupe.
250 $a 4th ed.
260 $a Singapore : $b World Scientific Publishing, $c c2019.
300 $a 1 online resource (440 p.) : $b ill.
490 1 $a Advanced series in circuits and systems ; $v vol. 8
504 $a Includes bibliographical references (p. 401-414) and indexes.
520 $a "The field of Artificial Neural Networks is the fastest growing field in Information Technology and specifically, in Artificial Intelligence and Machine Learning. This must-have compendium presents the theory and case studies of artificial neural networks. The volume, with 4 new chapters, updates the earlier edition by highlighting recent developments in Deep-Learning Neural Networks, which are the recent leading approaches to neural networks. Uniquely, the book also includes case studies of applications of neural networks — demonstrating how such case studies are designed, executed and how their results are obtained. The title is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers in medicine, finance and data mining."-- $c Publisher's website.
588 $a Title from web page (viewed April 9, 2019)
650 0 $a Neural networks (Computer science) $3 528588
830 0 $a Advanced series in circuits and systems ; $v v. 8 $3 1294970
856 4 0 $u https://www.worldscientific.com/worldscibooks/10.1142/11306#t=toc

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