Machine learning on commodity tiny devices: theory and practice
Auteur :
Guo, Song / Zhou, Qihua
Éditeur :
Taylor & Francis Ltd
ISBN :
9781032374260
Date de publication :
19 déc. 2024
Dimensions :
25,4 x 17,8 cm
Poids :
453 g
Langue :
Anglais
Pays d'origine :
Grande Bretagne
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.