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Deep learning = concepts and archite...

Pedrycz, Witold.

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Deep learning = concepts and architectures /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Deep learning/ edited by Witold Pedrycz, Shyi-Ming Chen.
Reminder of title:	concepts and architectures /
other author:	Pedrycz, Witold.
Published:	Cham :Springer International Publishing : : 2020.,
Description:	xii, 342 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Preface -- Chapter 1. Deep Learning Architectures -- Chapter 2. Theoretical Characterization of Deep Neural Networks -- Chapter 3. Scaling Analysis of Specialized Tensor Processing Architectures for Deep Learning Models, etc.
Contained By:	Springer eBooks
Subject:	Machine learning. -
Online resource:	https://doi.org/10.1007/978-3-030-31756-0
ISBN:	9783030317560

Deep learning = concepts and architectures /
Deep learningconcepts and architectures /[electronic resource] :edited by Witold Pedrycz, Shyi-Ming Chen. - Cham :Springer International Publishing :2020. - xii, 342 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.8661860-949X ;. - Studies in computational intelligence ;v.866..

Preface -- Chapter 1. Deep Learning Architectures -- Chapter 2. Theoretical Characterization of Deep Neural Networks -- Chapter 3. Scaling Analysis of Specialized Tensor Processing Architectures for Deep Learning Models, etc.

This book introduces readers to the fundamental concepts of deep learning and offers practical insights into how this learning paradigm supports automatic mechanisms of structural knowledge representation. It discusses a number of multilayer architectures giving rise to tangible and functionally meaningful pieces of knowledge, and shows how the structural developments have become essential to the successful delivery of competitive practical solutions to real-world problems. The book also demonstrates how the architectural developments, which arise in the setting of deep learning, support detailed learning and refinements to the system design. Featuring detailed descriptions of the current trends in the design and analysis of deep learning topologies, the book offers practical guidelines and presents competitive solutions to various areas of language modeling, graph representation, and forecasting.

ISBN: 9783030317560

Standard No.: 10.1007/978-3-030-31756-0doiSubjects--Topical Terms:

533906
Machine learning.

LC Class. No.: Q325.5

Dewey Class. No.: 006.3

Deep learning = concepts and architectures /
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245 0 0 $a Deep learning $h [electronic resource] : $b concepts and architectures / $c edited by Witold Pedrycz, Shyi-Ming Chen.
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300 $a xii, 342 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-949X ; $v v.866
505 0 $a Preface -- Chapter 1. Deep Learning Architectures -- Chapter 2. Theoretical Characterization of Deep Neural Networks -- Chapter 3. Scaling Analysis of Specialized Tensor Processing Architectures for Deep Learning Models, etc.
520 $a This book introduces readers to the fundamental concepts of deep learning and offers practical insights into how this learning paradigm supports automatic mechanisms of structural knowledge representation. It discusses a number of multilayer architectures giving rise to tangible and functionally meaningful pieces of knowledge, and shows how the structural developments have become essential to the successful delivery of competitive practical solutions to real-world problems. The book also demonstrates how the architectural developments, which arise in the setting of deep learning, support detailed learning and refinements to the system design. Featuring detailed descriptions of the current trends in the design and analysis of deep learning topologies, the book offers practical guidelines and presents competitive solutions to various areas of language modeling, graph representation, and forecasting.
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700 1 $a Pedrycz, Witold. $3 899642
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950 $a Intelligent Technologies and Robotics (Springer-42732)