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9783031195709 - Embedded Machine Learning for Cyber-physical, Iot, and Edge Computing: Hardware Architectures (10 results)
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Condition: good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.
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Condition: New. 2024th edition NO-PA16APR2015-KAP.
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Taschenbuch. Condition: Neu. Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing | Hardware Architectures | Sudeep Pasricha (u. a.) | Taschenbuch | xiv | Englisch | 2024 | Springer | EAN 9783031195709 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing : Hardware Architectures
Language: English
Published by Springer International Publishing, Springer International Publishing, 2024
ISBN 10: 3031195701 ISBN 13: 9783031195709
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits.
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Condition: new. Questo è un articolo print on demand.
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Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing
Language: English
Published by Springer International Publishing, Springer International Publishing Okt 2024, 2024
ISBN 10: 3031195701 ISBN 13: 9783031195709
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits. 428 pp. Englisch.
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Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing
Language: English
Published by Springer Verlag GmbH, 2024
ISBN 10: 3031195701 ISBN 13: 9783031195709
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.
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Condition: New. Print on Demand.
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Condition: New. PRINT ON DEMAND.
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Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing
Language: English
Published by Springer, Springer International Publishing Okt 2024, 2024
ISBN 10: 3031195701 ISBN 13: 9783031195709
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 428 pp. Englisch.
