Machine Learning on Commodity Tiny Devices
Song Guo
Sold by PBShop.store US, Wood Dale, IL, U.S.A.
AbeBooks Seller since April 7, 2005
New - Hardcover
Condition: New
Ships within U.S.A.
Quantity: Over 20 available
Add to basketSold by PBShop.store US, Wood Dale, IL, U.S.A.
AbeBooks Seller since April 7, 2005
Condition: New
Quantity: Over 20 available
Add to basketNew Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Seller Inventory # L1-9781032374239
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.
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.
"About this title" may belong to another edition of this title.
Returns Policy
We ask all customers to contact us for authorisation should they wish to return their order. Orders returned without authorisation may not be credited.
If you wish to return, please contact us within 14 days of receiving your order to obtain authorisation.
Returns requested beyond this time will not be authorised.
Our team will provide full instructions on how to return your order and once received our returns department will process your refund.
Please note the cost to return any...
Books are shipped from UK warehouse. Delivery thereafter is between 4 and 14 business days dependant upon your location - please do contact us with any queries you may have.
| Order quantity | 7 to 14 business days | 7 to 14 business days |
|---|---|---|
| First item | US$ 0.00 | US$ 0.00 |
Delivery times are set by sellers and vary by carrier and location. Orders passing through Customs may face delays and buyers are responsible for any associated duties or fees. Sellers may contact you regarding additional charges to cover any increased costs to ship your items.