Deep Learning: Algorithms and Applications
(Sprache: Englisch)
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...
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Klappentext zu „Deep Learning: Algorithms and Applications “
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.
Inhaltsverzeichnis zu „Deep Learning: Algorithms and Applications “
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.Bibliographische Angaben
- 2019, 1st ed. 2020, XII, 360 Seiten, 139 farbige Abbildungen, Maße: 15,9 x 23,9 cm, Gebunden, Englisch
- Herausgegeben: Witold Pedrycz, Shyi-Ming Chen
- Verlag: Springer, Berlin
- ISBN-10: 3030317595
- ISBN-13: 9783030317591
Sprache:
Englisch
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