Table of Contents
Preface
Chapter 1: Getting Started with TinyML
Technical requirements
Introducing TinyML
What is TinyML?
Why ML on microcontrollers?
Why run ML locally?
The opportunities and challenges for TinyML
Deployment environments for TinyML
tinyML Foundation
Summary of DL
Deep neural networks
Convolutional neural networks
Quantization
Learning the difference between power and energy
Voltage versus current
Power versus energy
Programming microcontrollers
Memory architecture
Peripherals
Presenting Arduino Nano 33 BLE Sense and Raspberry Pi Pico
Setting up Arduino Web Editor, TensorFlow, and Edge Impulse
Getting ready with Arduino Web Editor
Getting ready with TensorFlow
Getting ready with Edge Impulse
How to do it…
Running a sketch on ...
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