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Deep learning = concepts and archite...

Pedrycz, Witold.

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Deep learning = concepts and architectures /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Deep learning/ edited by Witold Pedrycz, Shyi-Ming Chen.
其他題名:	concepts and architectures /
其他作者:	Pedrycz, Witold.
出版者:	Cham :Springer International Publishing : : 2020.,
面頁冊數:	xii, 342 p. :ill. (some col.), digital ;24 cm.
內容註:	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
標題:	Machine learning. -
電子資源:	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

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