
Deep Learning: Algorithms and Applications
Springer (Publisher)
Published on 4. November 2019
Book
Hardback
XII, 360 pages
978-3-030-31759-1 (ISBN)
Description
This book presents a wealth of deep-learning algorithms and demonstrates their design process. It also highlights the need for a prudent alignment with the essential characteristics of the nature of learning encountered in the practical problems being tackled. Intended for readers interested in acquiring practical knowledge of analysis, design, and deployment of deep learning solutions to real-world problems, it covers a wide range of the paradigm's algorithms and their applications in diverse areas including imaging, seismic tomography, smart grids, surveillance and security, and health care, among others. Featuring systematic and comprehensive discussions on the development processes, their evaluation, and relevance, the book offers insights into fundamental design strategies for algorithms of deep learning.
More details
Product info
Book
Series
Edition
1st ed. 2020
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
139
32 s/w Abbildungen, 139 farbige Abbildungen
139 Illustrations, color; 32 Illustrations, black and white; XII, 360 p. 171 illus., 139 illus. in color.
Dimensions
Height: 241 mm
Width: 160 mm
Thickness: 26 mm
Weight
723 gr
ISBN-13
978-3-030-31759-1 (9783030317591)
DOI
10.1007/978-3-030-31760-7
Schweitzer Classification
Other editions
Additional editions

Witold Pedrycz | Shyi-Ming Chen
Deep Learning: Algorithms and Applications
Book
11/2020
Springer
€181.89
Shipment within 7-9 days

Witold Pedrycz | Shyi-Ming Chen
Deep Learning: Algorithms and Applications
E-Book
10/2019
Springer
€171.19
Available for download
Content
Preface.- Chapter 1. Activation Functions.- Chapter 2. Adversarial Examples in Deep Neural Networks: An Overview.- Chapter 3. Representation Learning in Power Time Series Forecasting, etc.