Items related to Embedded Machine Learning
Synopsis
This book represents a first step towards embedded machine learning. It presents techniques for optimizing and compressing deep learning models. These techniques make it easier to deploy a high-performance, lightweight deep learning model on resource-constrained devices such as smartphones and microcontrollers. This paper also explores a topical knowledge transfer technique, namely knowledge distillation. This technique makes it possible to improve the performance of a lightweight deep learning model, while transferring to it the knowledge of a complex, high-performance deep learning model. All these techniques have been detailed in this book and illustrated with practical Python implementations, generally based on the use of the pytorch and tensorflow libraries.
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Embedded Machine Learning
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Our Knowledge Publishing, 2024
ISBN 10: 6208158656
ISBN 13: 9786208158651
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Embedded Machine Learning
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PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Seller Inventory # L0-9786208158651
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Embedded Machine Learning
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Embedded Machine Learning
Published by
Our Knowledge Publishing, 2024
ISBN 10: 6208158656
ISBN 13: 9786208158651
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Embedded Machine Learning
Published by
Our Knowledge Publishing, 2024
ISBN 10: 6208158656
ISBN 13: 9786208158651
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Embedded Machine Learning
Published by
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ISBN 10: 6208158656
ISBN 13: 9786208158651
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Embedded Machine Learning
Published by
Our Knowledge Publishing, 2024
ISBN 10: 6208158656
ISBN 13: 9786208158651
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Embedded Machine Learning
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Omniscriptum, Our Knowledge Publishing, 2024
ISBN 10: 6208158656
ISBN 13: 9786208158651
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book represents a first step towards embedded machine learning. It presents techniques for optimizing and compressing deep learning models. These techniques make it easier to deploy a high-performance, lightweight deep learning model on resource-constrained devices such as smartphones and microcontrollers. This paper also explores a topical knowledge transfer technique, namely knowledge distillation. This technique makes it possible to improve the performance of a lightweight deep learning model, while transferring to it the knowledge of a complex, high-performance deep learning model. All these techniques have been detailed in this book and illustrated with practical Python implementations, generally based on the use of the pytorch and tensorflow libraries. 56 pp. Englisch. Seller Inventory # 9786208158651
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Embedded Machine Learning
Published by
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ISBN 10: 6208158656
ISBN 13: 9786208158651
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Embedded Machine Learning
Published by
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ISBN 10: 6208158656
ISBN 13: 9786208158651
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Seller: Books Puddle, Woodside, NY, U.S.A.
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