TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers
$31.99
Description
Book Synopsis: Deep learning networks are getting smaller. Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in size—small enough to run on a microcontroller. With this practical book, you'll enter the field of TinyML, where deep learning and embedded systems combine to make astounding things possible with tiny devices.
As of early 2022, the supplemental code files are available at https://oreil.ly/XuIQ4.
Pete Warden and Daniel Situnayake explain how you can train models small enough to fit into any environment. Ideal for software and hardware developers who want to build embedded systems using machine learning, this guide walks you through creating a series of TinyML projects, step-by-step. No machine learning or microcontroller experience is necessary.
Build a speech recognizer, a camera that detects people, and a magic wand that responds to gestures. Work with Arduino and ultra-low-power microcontrollers. Learn the essentials of ML and how to train your own models. Train models to understand audio, image, and accelerometer data. Explore TensorFlow Lite for Microcontrollers, Google's toolkit for TinyML. Debug applications and provide safeguards for privacy and security. Optimize latency, energy usage, and model and binary size.
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Details
TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers is a groundbreaking book that brings together the world of deep learning and embedded systems. With the power of TinyML, you can now unleash the potential of tiny devices and create astonishing projects. Imagine building a speech recognizer, a camera that detects people, or a magic wand that responds to gestures. The possibilities are endless!
What sets this book apart is that it caters to both software and hardware developers, making it accessible to a wide range of audiences. You don't need any prior experience with machine learning or microcontrollers to dive into TinyML. Pete Warden and Daniel Situnayake guide you through step-by-step projects, teaching you the essentials of ML and showing you how to train your own models.
One of the highlights of this book is its focus on Arduino and ultra-low-power microcontrollers. You'll learn how to work with these devices and harness their capabilities to build powerful embedded systems. Whether you're a seasoned developer or a beginner, this guide will equip you with the knowledge and skills needed to create innovative projects with ease.
Furthermore, you'll explore TensorFlow Lite for Microcontrollers, Google's toolkit specifically designed for TinyML. This toolkit provides you with the necessary resources to optimize latency, energy usage, and model and binary size. You'll also learn how to debug applications, ensuring their performance and security, and discover ways to safeguard privacy.
Don't miss out on the amazing opportunities TinyML has to offer. Take your projects to the next level with TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers. Get your hands on this incredible book and start building groundbreaking embedded systems today!
Read more about TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers here.
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