TinyML: Machine Learning with TensorFlow Lite (O'Reilly)
Wednesday, 05 February 2020

This practical book, whose subtitle continues "on Arduino and Ultra-Low-Power Microcontrollers" looks at TinyML, where deep learning and embedded systems are combined with tiny devices. Authors Pete Warden and Daniel Situnayake explain how you can train models small enough to fit into any environment. Aimed at 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.

<ASIN:1492052043>

 

Authors: Pete Warden and Daniel Situnayake
Publisher: O'Reilly
Date: December 2019
Pages: 504
ISBN: 978-1492052043
Print: 1492052043
Kindle: B082TY3SX7
Audience: Developers interested in machine learning
Level: Intermediate
Category: Artificial Intelligence

Contents: 

  • 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

 

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