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

by Pete Warden and Daniel Situnayake

Copyright 2020 Pete Warden and Daniel Situnayake. All rights reserved.

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978-1-492-05204-3

[LSI]

Something about electronics has captured my imagination for as long as I can remember. Weve learned to dig rocks from the earth, refine them in mysterious ways, and produce a dizzying array of tiny components that we combineaccording to arcane lawsto imbue them with some essence of life.

To my eight-year-old mind, a battery, switch, and filament bulb were enchanting enough, let alone the processor inside my familys home computer. And as the years have passed, Ive developed some understanding of the principles of electronics and software that make these inventions work. But what has always struck me is the way a system of simple elements can come together to create a subtle and complex thing, and deep learning really takes this to new heights.

One of this books examples is a deep learning network that, in some sense, understands how to see. Its made up of thousands of virtual neurons, each of which follows some simple rules and outputs a single number. Alone, each neuron isnt capable of much, but combined, andthrough traininggiven a spark of human knowledge, they can make sense of our complex world.

Theres some magic in this idea: simple algorithms running on tiny computers made from sand, metal, and plastic can embody a fragment of human understanding. This is the essence of TinyML, a term that Pete coined and will introduce in . In the pages of this book, youll find the tools youll need to build these things yourself.

Thank you for being our reader. This is a complicated subject, but weve tried hard to keep things simple and explain all the concepts that youll need. We hope you enjoy what weve written, and were excited to see what you create!

Daniel Situnayake