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TinyML Cookbook

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

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Product type Paperback
Published in Nov 2023
Publisher Packt
ISBN-13 9781837637362
Length 664 pages
Edition 2nd Edition
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Author (1):
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Gian Marco Iodice Gian Marco Iodice
Author Profile Icon Gian Marco Iodice
Gian Marco Iodice
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Table of Contents (16) Chapters Close

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

Summary

The recipes presented in this chapter covered the basic principles of microcontroller programming, a prerequisite for the projects developed in the rest of this book.

In the first part, we learned how to use the microcontroller to transmit data serially to the computer for generating files to upload to Google Drive.

Then, our focus shifted to the principles of controlling the LED light through the GPIO peripheral. These recipes taught us how to build electronic circuits on the breadboard, determine the appropriate resistor based on the LED emitting light color, and program the GPIO peripheral to output digital signals.

Finally, we discovered how to attach a push-button to the microcontroller and program the GPIO peripheral to read its state. Upon completing this chapter, you should be well prepared to delve into developing your first tinyML project.

In the next chapter, we will implement a basic weather station to predict the occurrence of snowfall using the...

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