Witold (Hrsg.) Pedrycz
Deep Learning: Algorithms and Applications
Ebook (PDF Format)
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 comprehens…
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Beschreibung
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.
CHF 165.50
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Produktdetails
Weitere Autoren: Chen, Shyi-Ming (Hrsg.)
- ISBN: 978-3-030-31760-7
- EAN: 9783030317607
- Produktnummer: 32874773
- Verlag: Springer-Verlag GmbH
- Sprache: Englisch
- Erscheinungsjahr: 2019
- Seitenangabe: 360 S.
- Plattform: PDF
- Masse: 18'040 KB
- Abbildungen: 32 schwarz-weiße und 139 farbige Abbildungen, Bibliographie
- Reihenbandnummer: 865
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