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Deep learning networksdesign, development and deployment /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Deep learning networksby Jayakumar Singaram, S. S. Iyengar, Azad M. Madni.
Reminder of title:	design, development and deployment /
Author:	Singaram, Jayakumar.
other author:	Iyengar, S. S.
Published:	Cham :Springer Nature Switzerland :2024.
Description:	xxiii, 161 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Deep learning (Machine learning)
Online resource:	https://doi.org/10.1007/978-3-031-39244-3
ISBN:	9783031392443$q(electronic bk.)

Deep learning networksdesign, development and deployment /
Singaram, Jayakumar.

Deep learning networksdesign, development and deployment /[electronic resource] :by Jayakumar Singaram, S. S. Iyengar, Azad M. Madni. - Cham :Springer Nature Switzerland :2024. - xxiii, 161 p. :ill. (some col.), digital ;24 cm.

Introduction -- Deep Learning -- Brief survey on Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) -- Tool Set for Deep Learning Applications -- Data-Set Design and Data Labeling -- DL Model: Design and Development -- Training and Testing of DL Model -- Deploying DL in Jetson Nano -- Deploying DL in Android Phone -- Deploying DL in Ultra96-V2 Field Programmable Gate Array (FPGA) -- Conclusion.

This textbook presents multiple facets of design, development and deployment of deep learning networks for both students and industry practitioners. It introduces a deep learning tool set with deep learning concepts interwoven to enhance understanding. It also presents the design and technical aspects of programming along with a practical way to understand the relationships between programming and technology for a variety of applications. It offers a tutorial for the reader to learn wide-ranging conceptual modeling and programming tools that animate deep learning applications. The book is especially directed to students taking senior level undergraduate courses and to industry practitioners interested in learning about and applying deep learning methods to practical real-world problems. The unique features of this book are: Easy-to-understand description of the multiple facets of design, development and deployment of deep learning networks; Practical tools that facilitate understanding of underlying technology; Covers wide-ranging conceptual modeling and programming tools that animate deep learning applications.

ISBN: 9783031392443$q(electronic bk.)

Standard No.: 10.1007/978-3-031-39244-3doiSubjects--Topical Terms:

913129
Deep learning (Machine learning)

LC Class. No.: Q325.73

Dewey Class. No.: 006.31

Deep learning networksdesign, development and deployment /
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245 1 0 $a Deep learning networks $h [electronic resource] : $b design, development and deployment / $c by Jayakumar Singaram, S. S. Iyengar, Azad M. Madni.
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505 0 $a Introduction -- Deep Learning -- Brief survey on Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) -- Tool Set for Deep Learning Applications -- Data-Set Design and Data Labeling -- DL Model: Design and Development -- Training and Testing of DL Model -- Deploying DL in Jetson Nano -- Deploying DL in Android Phone -- Deploying DL in Ultra96-V2 Field Programmable Gate Array (FPGA) -- Conclusion.
520 $a This textbook presents multiple facets of design, development and deployment of deep learning networks for both students and industry practitioners. It introduces a deep learning tool set with deep learning concepts interwoven to enhance understanding. It also presents the design and technical aspects of programming along with a practical way to understand the relationships between programming and technology for a variety of applications. It offers a tutorial for the reader to learn wide-ranging conceptual modeling and programming tools that animate deep learning applications. The book is especially directed to students taking senior level undergraduate courses and to industry practitioners interested in learning about and applying deep learning methods to practical real-world problems. The unique features of this book are: Easy-to-understand description of the multiple facets of design, development and deployment of deep learning networks; Practical tools that facilitate understanding of underlying technology; Covers wide-ranging conceptual modeling and programming tools that animate deep learning applications.
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