Machine Learning on Commodity Tiny Devices - Theory and Practice

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.

List of contents

1. Introduction  2. Fundamentals: On-device Learning Paradigm  3. Preliminary: Theories and Algorithms  4. Model-level Design: Computation Acceleration and Communication Saving  5. Hardware-level Design: Neural Engines and Tensor Accelerators  6. Infrastructure-level Design: Serverless and Decentralized Machine Learning  7. System-level Design: from Standalone to Clusters  8. Application: Image-based Visual Perception  9. Application: Video-based Real-time Processing 10. Application: Privacy, Security, Robustness and Trustworthiness in Edge AI

About the author

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.

Summary

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.

Product details

• Authors: Song Guo, Song Zhou Guo, Guo Song, Qihua Zhou
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Paperback / Softback
• Released: 19.12.2024
• EAN: 9781032374260
• ISBN: 978-1-0-3237426-0
• No. of pages: 250
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > Data communication, networks; machine learning, Artificial Intelligence, COMPUTERS / Programming / Games, COMPUTERS / Hardware / Personal Computers / General, Games development & programming, Personal computers, COMPUTERS / Artificial Intelligence / General, Games development and programming, COMPUTERS / Data Science / Machine Learning