Machine Learning on Commodity Tiny Devices: Theory and Practice by Guo, Song

Machine Learning on Commodity Tiny Devices: Theory and Practice (Paperback) (ISBN-13: 9781032374260)

Vendor: Song Guo
Product type: Books
Format: Paperback
$63.99
$63.99
$63.99
Subtotal: $63.99
Machine Learning on Commodity Tiny Devices: Theory and Practice by Guo, Song

Machine Learning on Commodity Tiny Devices: Theory and Practice

$63.99
Machine Learning on Commodity Tiny Devices: Theory and Practice by Guo, Song

Machine Learning on Commodity Tiny Devices: Theory and Practice

$63.99
Format: Paperback
Description
Description
x

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: Song Guo,Qihua Zhou
ISBN-10: 1032374268
ISBN-13: 9781032374260
Publisher: CRC Press
Language: English
Published: 12/19/2024
Pages: 250
Format: Paperback
Weight: 1.04lbs
Size: 10.00h x 7.00w x 0.56d
By Song Guo
By Song Guo
x

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.

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