You're reading from TinyML Cookbook Combine machine learning with microcontrollers to solve real-world problems

Product type Paperback

Published in Nov 2023

Publisher Packt

ISBN-13 9781837637362

Length 664 pages

Edition 2nd Edition

Languages

Python

Tools

Combine

Concepts

Machine Learning

Author (1):

Gian Marco Iodice

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Table of Contents (16) Chapters

Preface

1. Getting Ready to Unlock ML on Microcontrollers FREE CHAPTER

2. Unleashing Your Creativity with Microcontrollers

3. Building a Weather Station with TensorFlow Lite for Microcontrollers

4. Using Edge Impulse and the Arduino Nano to Control LEDs with Voice Commands

5. Recognizing Music Genres with TensorFlow and the Raspberry Pi Pico – Part 1

6. Recognizing Music Genres with TensorFlow and the Raspberry Pi Pico – Part 2

7. Detecting Objects with Edge Impulse Using FOMO on the Raspberry Pi Pico

8. Classifying Desk Objects with TensorFlow and the Arduino Nano

9. Building a Gesture-Based Interface for YouTube Playback with Edge Impulse and the Raspberry Pi Pico

10. Deploying a CIFAR-10 Model for Memory-Constrained Devices with the Zephyr OS on QEMU

11. Running ML Models on Arduino and the Arm Ethos-U55 microNPU Using Apache TVM

12. Enabling Compelling tinyML Solutions with On-Device Learning and scikit-learn on the Arduino Nano and Raspberry Pi Pico

13. Conclusion

14. Other Books You May Enjoy

15. Index

Running ML Models on Arduino and the Arm Ethos-U55 microNPU Using Apache TVM

In all our projects developed so far, we have relied on TensorFlow Lite for Microcontrollers (tflite-micro) as a software stack to deploy machine learning (ML) models on the Arduino Nano, Raspberry Pi Pico, and SparkFun Artemis Nano. However, other frameworks are available within the open-source community for this scope. Among these alternatives, Apache TVM (or simply TVM) has gained considerable attraction due to its ability to generate optimized code tailored to the desired target platform.

In this chapter, we will explore how to leverage this technology to deploy a quantized CIFAR-10 TensorFlow Lite model in various scenarios.

The chapter will start by giving an overview of Arduino Command Line Interface (CLI), an indispensable tool to compile and run the code generated by TVM on any Arduino-compatible platform.

After introducing Arduino CLI, we will present TVM by showing how to generate C...

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You're reading from TinyML Cookbook Combine machine learning with microcontrollers to solve real-world problems

Table of Contents (16) Chapters

Running ML Models on Arduino and the Arm Ethos-U55 microNPU Using Apache TVM

Authors (1)

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You're reading from TinyML Cookbook Combine machine learning with microcontrollers to solve real-world problems

Table of Contents (16) Chapters

Running ML Models on Arduino and the Arm Ethos-U55 microNPU Using Apache TVM

Unlock this book and the full library FREE for 7 days

Authors (1)

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