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Databases & Big Data - TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers

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. 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

Details

Are you ready to unlock the incredible potential of TinyML and take your projects to new heights? Dive into the world of machine learning with TensorFlow Lite on Arduino and ultra-low-power microcontrollers with this groundbreaking book. Discover how deep learning networks are shrinking to fit on tiny devices, enabling you to create innovative solutions that were once unimaginable. Don't miss out on the opportunity to be at the forefront of this cutting-edge technology!

Join authors Pete Warden and Daniel Situnayake on a journey to explore the limitless possibilities of TinyML. Whether you're a seasoned developer or just starting out, this book will guide you through building speech recognizers, smart cameras, and gesture-controlled devices using Arduino and microcontrollers. No prior experience in machine learning or microcontrollers? No problem! This comprehensive guide will provide all the tools and knowledge you need to get started.

With TensorFlow Lite for Microcontrollers at your fingertips, you'll learn how to train models to understand audio, images, and sensor data, opening up a world of creative opportunities. Dive into the world of TinyML, optimize energy usage, reduce latency, and enhance privacy and security in your projects. Take the first step towards realizing your dream of creating powerful embedded systems with the help of this must-have book!

Get your copy now and revolutionize your projects with TinyML!

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