TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers

TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers Pete Warden, Daniel Situnayake
Deep learning networks are getting smaller. Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in size—small enough to run on a microcontroller. With this practical book you’ll enter the field of TinyML, where deep learning and embedded systems combine to make astounding things possible with tiny devices.Pete Warden and Daniel Situnayake explain how you can train models small enough to fit into any environment. Ideal for software and hardware developers who want to build embedded systems using machine learning, this guide walks you through creating a series of TinyML projects, step-by-step. No machine learning or microcontroller experience is necessary.• Build a speech recognizer, a camera that detects people, and a magic wand that responds to gestures
• Work with Arduino and ultra-low-power microcontrollers
• Learn the essentials of ML and how to train your own models
• Train models to understand audio, image, and accelerometer data
• Explore TensorFlow Lite for Microcontrollers, Google’s toolkit for TinyML
• Debug applications and provide safeguards for privacy and security
• Optimize latency, energy usage, and model and binary size Categories:
Computers – Cybernetics
Year:
2019
Edition:
1
Publisher:
O’Reilly Media
Language:
english
Pages:
484 / 504
ISBN 10:
1492052043
ISBN 13:
9781492052043
File:
243 MB