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Deep Learning Networks [electronic resource] : Design, Development and Deployment / by Jayakumar Singaram, S. S. Iyengar, Azad M. Madni.

By: Contributor(s): Material type: TextPublisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edition: 1st ed. 2024Description: XXIII, 161 p. 71 illus., 70 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783031392443
Subject(s):
Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleLOC classification:
  • TK5101-5105.9
Online resources:
Contents:
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.
In: Springer Nature eBookSummary: 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.
Item type: List(s) this item appears in: Titluri cărți electronice Springer Nature 2025 (10631 titluri)
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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.

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