Applied TinyML - End-to-end machine learning for microcontrollers with examples

This book will guide you through building these smart devices. It establishes TinyML''s core foundations and a methodology for application development, from problem definition to power management and cost analysis. You will explore practical skills applications, learning sound, movement, and image classification, followed by advanced techniques like object tracking and sensor fusion, using methods such as Kalman filters. You will explore deep learning regression for predictive tasks and essential anomaly detection for identifying unusual patterns, all demonstrated through real-world use cases.