Machine Learning on Commodity Tiny Devices: Theory and Practice

Machine Learning on Commodity Tiny Devices: Theory and Practice - Hardcover

$172.42
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Machine Learning on Commodity Tiny Devices: Theory and Practice

Machine Learning on Commodity Tiny Devices: Theory and Practice - Hardcover

$172.42
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by Song Guo (Author), Qihua Zhou (Author)

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.

Author Biography

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 Engineering, Fellow of the IEEE, Fellow of the AAIA and Clarivate Highly Cited Researcher.

Qihua Zhou is a PhD student with the Department of Computing at the Hong Kong Polytechnic University. His research interests include distributed AI systems, large-scale parallel processing, TinyML systems and domain-specific accelerators.

Number of Pages: 250
Dimensions: 0.63 x 10 x 7 IN
Illustrated: Yes
Publication Date: December 13, 2022

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