Machine Learning Commodity Tiny by Guo Song (29 results)
- Softcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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- Softcover
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- Softcover
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- Softcover
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- Softcover
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- Softcover
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- Softcover
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- Softcover
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- Hardcover
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- Softcover
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- Hardcover
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- Hardcover
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- Hardcover
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- Hardcover
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- Hardcover
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- Hardcover
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Condition: New. 1st edition NO-PA16APR2015-KAP.
- Hardcover
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More images- Softcover
Seller: preigu, Osnabrück, Germanypreigu
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Taschenbuch. Condition: Neu. Machine Learning on Commodity Tiny Devices | Theory and Practice | Song Guo (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2024 | CRC Press | EAN 9781032374260 | Verantwortliche Person für die EU: Taylor & Francis Verlag GmbH, Kaufingerstr. 24, 80331 München, gpsr[at]taylorandfrancis…[dot]com | Anbieter: preigu.
- Hardcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Hardcover. Condition: Brand New. 249 pages. 10.00x7.00x0.75 inches. In Stock.
- Softcover
- Print on Demand
Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
- Softcover
- Print on Demand
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
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PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
- Softcover
- Print on Demand
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book aims at the tiny machine learning (TinyML) software and hardware synergy for edge intelligence applications. This book presents on-device learning techniques covering model-level neural network design, algorithm-level trai…ning optimization and hardware-level instruction acceleration.Analyzing the limitations of conventional in-cloud computing would reveal that on-device learning is a promising research direction to meet the requirements of edge intelligence applications. As to the cutting-edge research of TinyML, implementing a high-efficiency learning framework and enabling system-level acceleration is one of the most fundamental issues. This book presents a comprehensive discussion of the latest research progress and provides system-level insights on designing TinyML frameworks, including neural network design, training algorithm optimization and domain-specific hardware acceleration. It identifies the main challenges when deploying TinyML tasks in the real world and guides the researchers to deploy a reliable learning system.This book will be of interest to students and scholars in the field of edge intelligence, especially to those with sufficient professional Edge AI skills. It will also be an excellent guide for researchers to implement high-performance TinyML systems. 268 pp. Englisch.
- Hardcover
- Print on Demand
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
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US$ 128.99
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HRD. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
- Hardcover
- Print on Demand
Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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HRD. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
- Softcover
- Print on Demand
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book aims at the tiny machine learning (TinyML) software and hardware synergy for edge intelligence applications. This book presents on-device learning techniques covering model-level neural network design, algorithm-level training…optimization and hardware-level instruction acceleration.Analyzing the limitations of conventional in-cloud computing would reveal that on-device learning is a promising research direction to meet the requirements of edge intelligence applications. As to the cutting-edge research of TinyML, implementing a high-efficiency learning framework and enabling system-level acceleration is one of the most fundamental issues. This book presents a comprehensive discussion of the latest research progress and provides system-level insights on designing TinyML frameworks, including neural network design, training algorithm optimization and domain-specific hardware acceleration. It identifies the main challenges when deploying TinyML tasks in the real world and guides the researchers to deploy a reliable learning system.This book will be of interest to students and scholars in the field of edge intelligence, especially to those with sufficient professional Edge AI skills. It will also be an excellent guide for researchers to implement high-performance TinyML systems.
- Hardcover
- Print on Demand
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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Condition: New. PRINT ON DEMAND.
- Hardcover
- Print on Demand
Seller: moluna, Greven, Germanymoluna
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US$ 98.67
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Song Guo is a Full Professor leading the Edge Intelligence Lab and Research Group of Networking and Mobile Computing at the Hong Kong Polytechnic University. Professor Guo is a Fellow of the Canadian Academy of Engine…ering, Fellow of the.
- Hardcover
- Print on Demand
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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US$ 163.73
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Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book aims at the tiny machine learning (TinyML) software and hardware synergy for edge intelligence applications. It presents on-device learning techniques covering model-level neural network design, algorithm-level training optimization,…and hardware-level instruction acceleration.
