Deep Learning: Concepts and Architectures

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Synopsis

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.

Book details

Edition:
1st ed. 2020
Series:
Studies in Computational Intelligence (Book 866)
Author:
Witold Pedrycz, Shyi-Ming Chen
ISBN:
9783030317560
Related ISBNs:
9783030317553
Publisher:
Springer International Publishing
Pages:
N/A
Reading age:
Not specified
Includes images:
Yes
Date of addition:
2019-10-30
Usage restrictions:
Copyright
Copyright date:
2020
Copyright by:
Springer Nature Switzerland AG 
Adult content:
No
Language:
English
Categories:
Computers and Internet, Nonfiction, Technology