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Deep Learning: Concepts and Architectures

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Deep Learning: Concepts and Architectures/ edited by Witold Pedrycz, Shyi-Ming Chen.
其他作者:	Chen, Shyi-Ming.
面頁冊數:	XII, 342 p. 135 illus., 95 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Artificial Intelligence. -
電子資源:	https://doi.org/10.1007/978-3-030-31756-0
ISBN:	9783030317560

Deep Learning: Concepts and Architectures
Deep Learning: Concepts and Architectures[electronic resource] /edited by Witold Pedrycz, Shyi-Ming Chen. - 1st ed. 2020. - XII, 342 p. 135 illus., 95 illus. in color.online resource. - Studies in Computational Intelligence,8661860-949X ;. - Studies in Computational Intelligence,564.

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:

646849
Artificial Intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

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