Book Image

TinyML Cookbook

By : Gian Marco Iodice
Book Image

TinyML Cookbook

By: Gian Marco Iodice

Overview of this book

This book explores TinyML, a fast-growing field at the unique intersection of machine learning and embedded systems to make AI ubiquitous with extremely low-powered devices such as microcontrollers. The 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, supplying power to microcontrollers with batteries, and more. Next, you’ll cover recipes relating to temperature, humidity, and the three “V” sensors (Voice, Vision, and Vibration) to gain the necessary skills to implement end-to-end smart applications in different scenarios. Later, you’ll learn best practices for building tiny models for memory-constrained microcontrollers. Finally, you’ll explore two of the most recent technologies, microTVM and microNPU that will help you step up your TinyML game. By the end of this book, you’ll be well-versed with best practices and machine learning frameworks to develop ML apps easily on microcontrollers and have a clear understanding of the key aspects to consider during the development phase.
Table of Contents (10 chapters)

Chapter 1: Getting Started with TinyML

Here we are, with our first step into the world of TinyML.

This chapter starts with an overview of this emerging field, presenting the opportunities and challenges to bring machine learning (ML) to extremely low-power microcontrollers.

The body of this chapter focuses on the fundamental elements behind ML, power consumption, and microcontrollers that make TinyML unique and different from conventional ML in the cloud, desktops, or even smartphones. In particular, the Programming microcontrollers section will be crucial for those with little experience in embedded programming.

After introducing the TinyML building blocks, we shall set up the development environment for a simple LED application, which will officially mark the beginning of our practical TinyML journey.

In contrast to what we will find in the following chapters, this chapter has a more theoretical structure to get you familiar with the concepts and terminology of this fast...