TY  - BOOK
AU  - Warden,Pete
AU  - Situnayake,Daniel
TI  - TinyML: machine learning with tensorflow lite on arduino and ultra-low-power microcontrollers 
SN  - 9789352139606 (PBK)
U1  - 006.31 
PY  - 2021///
CY  - Mumbai
PB  - O'Relly Media Inc.
KW  - Machine learning
KW  - Signal processing
KW  - Digital techniques
KW  - Microcontrollers
N1  - Includes bibliographical references and index; Introduction -- Getting started -- Getting up to speed on machine learning -- The "Hello world" of TinyML : building and training a model -- The "Hello world" of TinyML : building an application -- The "Hello world" of TinyML : deploying to microcontrollers -- Wake-word detection : building an application -- Wake-word detection : training a model -- Person detection : building an application -- Person detection : training a model -- Magic wand : building an application -- Magic wand : training a model -- TensorFlow lite for microcontrollers -- Designing your own TinyML applications -- Optimizing latency -- Optimizing energy usage -- Optimizing model and binary size -- Debugging -- Porting models from TensorFlow to TensorFlow Lite -- Privacy, security, and deployment -- Learning more
N2  - Deep learning networks are becoming smaller, with models as small as 14 kilobytes. This practical book, TinyML, combines deep learning and embedded systems to create small, portable devices. It provides a step-by-step guide for developers to create TinyML projects, including speech recognition, camera detection, and gesture response. The book also covers learning ML basics, using TensorFlow Lite for microcontrollers, and optimizing latency and energy usage
ER  -