Preface

This book is about TinyML, a fast-growing field at the unique intersection of machine learning (ML) and embedded systems to make AI work with extremely low-powered devices, such as microcontrollers.

TinyML is an exciting field full of opportunities. With a small budget, we can give life to objects that interact with the world around us smartly and transform the way we live for the better. However, this field can be hard to approach if we come from an ML background with little familiarity with embedded systems, such as microcontrollers. Therefore, this book aims to dispel these barriers and make TinyML also accessible to developers with no embedded programming experience through practical examples. Each chapter will be a self-contained project to learn how to use some of the technologies at the heart of TinyML, interface with electronic components such as sensors, and deploy ML models on memory-constrained devices.

TinyML Cookbook starts with a practical introduction to this multidisciplinary field to get you up to speed with some of the fundamentals for deploying intelligent applications on Arduino Nano 33 BLE Sense and Raspberry Pi Pico. As you progress, you'll tackle various problems that you may encounter while prototyping microcontrollers, such as controlling the LED state with GPIO and a push-button and supplying power to microcontrollers with batteries. After that, you'll cover recipes relating to temperature, humidity, and the three V (voice, vision, and vibration) sensors to gain the necessary skills to implement end-to-end smart applications in different scenarios. Then, you'll learn best practices to build tiny models for memory-constrained microcontrollers. Finally, you'll explore two of the most recent technologies, microTVM and microNPU, which will help you step up your TinyML game.

By the end of this book, you'll be well versed in best practices and ML frameworks to develop ML apps easily on microcontrollers and have a clear understanding of the key aspects to consider during the development phase.