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TinyML Cookbook

You're reading from TinyML Cookbook Combine artificial intelligence and ultra-low-power embedded devices to make the world smarter

Product type Paperback

Published in Apr 2022

Publisher Packt

ISBN-13 9781801814973

Length 344 pages

Edition 1st Edition

Tools

Combine

Concepts

Artificial Intelligence

Author (1):

Gian Marco Iodice

View More author details

Table of Contents (10) Chapters

Preface

1. Chapter 1: Getting Started with TinyML

2. Chapter 2: Prototyping with Microcontrollers FREE CHAPTER

3. Chapter 3: Building a Weather Station with TensorFlow Lite for Microcontrollers

4. Chapter 4: Voice Controlling LEDs with Edge Impulse

5. Chapter 5: Indoor Scene Classification with TensorFlow Lite for Microcontrollers and the Arduino Nano

6. Chapter 6: Building a Gesture-Based Interface for YouTube Playback

7. Chapter 7: Running a Tiny CIFAR-10 Model on a Virtual Platform with the Zephyr OS

8. Chapter 8: Toward the Next TinyML Generation with microNPU

9. Other Books You May Enjoy

Presenting Arduino Nano 33 BLE Sense and Raspberry Pi Pico

A microcontroller board is a printed circuit board (PCB) that combines the microcontroller with the necessary electronic circuit to make it ready to use. In some cases, the microcontroller board could integrate additional devices to target specific end applications.

Arduino Nano 33 BLE Sense (in short, Arduino Nano) and Raspberry Pico are the microcontroller boards used in this book.

Arduino Nano, designed by Arduino (https://www.arduino.cc), is a board that combines a microcontroller (nRF52840) powered by an Arm Cortex-M4 processor with several sensors and Bluetooth radio for an easy TinyML development experience. We will require just a few additional external components when developing on Arduino Nano since most are already available on-board.

Raspberry Pi Pico, designed by the Raspberry Pi Foundation (https://www.raspberrypi.org), does not provide sensors and the Bluetooth module on-board. Still, it has a microcontroller...

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Authors (1)

Gian Marco Iodice

Gian Marco Iodice

Gian Marco Iodice is team and tech lead in the Machine Learning Group at Arm, who co-created the Arm Compute Library in 2017. The Arm Compute Library is currently the most performant library for ML on Arm, and it's deployed on billions of devices worldwide – from servers to smartphones. Gian Marco holds an MSc degree, with honors, in electronic engineering from the University of Pisa (Italy) and has several years of experience developing ML and computer vision algorithms on edge devices. Now, he's leading the ML performance optimization on Arm Mali GPUs. In 2020, Gian Marco cofounded the TinyML UK meetup group to encourage knowledge-sharing, educate, and inspire the next generation of ML developers on tiny and power-efficient devices.

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