Gian Marco Iodice 
TinyML Cookbook [EPUB ebook] 
Combine machine learning with microcontrollers to solve real-world problems

<p><b>Over 70 recipes to help you develop smart applications on Arduino Nano 33 BLE Sense, Raspberry Pi Pico, and Spark Fun Red Board Artemis Nano using the power of machine learning Purchase of the print or Kindle book includes a free e Book in PDF format.</b></p><h4>Key Features</h4><ul><li>Over 20+ new recipes, including recognizing music genres and detecting objects in a scene</li><li>Create practical examples using Tensor Flow Lite for Microcontrollers, Edge Impulse, and more</li><li>Explore cutting-edge technologies, such as on-device training for updating models without data leaving the device</li></ul><h4>Book Description</h4>Discover the incredible world of tiny Machine Learning (tiny ML) and create smart projects using real-world data sensors with the Arduino Nano 33 BLE Sense, Raspberry Pi Pico, and Spark Fun Red Board Artemis Nano.Tiny ML Cookbook, Second Edition, will show you how to build unique end-to-end ML applications using temperature, humidity, vision, audio, and accelerometer sensors in different scenarios. These projects will equip you with the knowledge and skills to bring intelligence to microcontrollers. You»ll train custom models from weather prediction to real-time speech recognition using Tensor Flow and Edge Impulse.Expert tips will help you squeeze ML models into tight memory budgets and accelerate performance using CMSIS-DSP.This improved edition includes new recipes featuring an LSTM neural network to recognize music genres and the Faster-Objects-More-Objects (FOMO) algorithm for detecting objects in a scene. Furthermore, you’ll work on scikit-learn model deployment on microcontrollers, implement on-device training, and deploy a model using micro TVM, including on a micro NPU. This beginner-friendly and comprehensive book will help you stay up to date with the latest developments in the tiny ML community and give you the knowledge to build unique projects with microcontrollers!<h4>What you will learn</h4><ul><li>Understand the microcontroller programming fundamentals</li><li>Work with real-world sensors, such as the microphone, camera, and accelerometer</li><li>Implement an app that responds to human voice or recognizes music genres</li><li>Leverage transfer learning with FOMO and Keras</li><li>Learn best practices on how to use the CMSIS-DSP library</li><li>Create a gesture-recognition app to build a remote control</li><li>Design a CIFAR-10 model for memory-constrained microcontrollers</li><li>Train a neural network on microcontrollers</li></ul><h4>Who this book is for</h4><p>This book is ideal for machine learning engineers or data scientists looking to build embedded/edge ML applications and Io T developers who want to add machine learning capabilities to their devices. If you’re an engineer, student, or hobbyist interested in exploring tiny ML, then this book is your perfect companion.Basic familiarity with C/C++ and Python programming is a prerequisite; however, no prior knowledge of microcontrollers is necessary to get started with this book.</p>