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Titlebook: Deep Learning Networks; Design, Development Jayakumar Singaram,S. S. Iyengar,Azad M. Madni Textbook 2024 The Editor(s) (if applicable) and

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發(fā)表于 2025-3-21 16:27:11 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Deep Learning Networks
副標題Design, Development
編輯Jayakumar Singaram,S. S. Iyengar,Azad M. Madni
視頻videohttp://file.papertrans.cn/265/264577/264577.mp4
概述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
圖書封面Titlebook: Deep Learning Networks; Design, Development  Jayakumar Singaram,S. S. Iyengar,Azad M. Madni Textbook 2024 The Editor(s) (if applicable) and
描述.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.?.
出版日期Textbook 2024
關(guān)鍵詞Deep Learning; Artificial Intelligence (AI); Machine Learning (ML); Data Labeling; Deep Learning Applica
版次1
doihttps://doi.org/10.1007/978-3-031-39244-3
isbn_softcover978-3-031-39246-7
isbn_ebook978-3-031-39244-3
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Efficient Organizational Designachines like DGX Station A100 or higher versions. Further, also demonstrates and showcases how to create, build and configure dockers for large network model including the support services (J. S, Handling deployment of deep nearnign networks in edge devices, 2018. .).
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發(fā)表于 2025-3-22 12:03:27 | 只看該作者
Training of Deep Learning Networks,achines like DGX Station A100 or higher versions. Further, also demonstrates and showcases how to create, build and configure dockers for large network model including the support services (J. S, Handling deployment of deep nearnign networks in edge devices, 2018. .).
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發(fā)表于 2025-3-22 15:50:58 | 只看該作者
acilitate understanding of underlying technology.Covers wide.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 u
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Meenakshi Mishra,Deepak John Mathew presents an introduction to deep learning in the context of deep programming with an emphasis on learning algorithms for many real-time applications. More specifically, it provides a clear direction towards an introduction path forward application and the art of science and engineering application programming.
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,Ausgew?hlte Rahmenbedingungen,plication deployment. More importantly, sample AI application deployment includes quick-look IBM WATSON, IBM Watson service, and monitor tomato farm and real-time audit of IP networks. Agriworks work flow complexity for diagnosis is used using a smartphone application with a few clicks.
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Wirtschaftswissenschaftliche Beitr?geupyter Notebook in various environments. More importantly, the practical training of tool engagement for deep learning is inevitable for students, professionals, domain experts, and data scientists which is highly recommended to gain the best learning experience.
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