{"product_id":"tinyml-cookbook-second-edition-combine-machine-learning-with-microcontrollers-to-solve-real-world-problems-9781837637362","title":"TinyML Cookbook - Second Edition: Combine machine learning with microcontrollers to solve real-world problems","description":"\u003cp\u003e\u003cstrong\u003eOver 70 recipes to help you develop smart applications on Arduino Nano 33 BLE Sense, Raspberry Pi Pico, and SparkFun RedBoard Artemis Nano using the power of machine learning\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003ePurchase of the print or Kindle book includes a free eBook in PDF format.\u003c\/strong\u003e\u003c\/p\u003eKey Features\u003cul\u003e\n\u003cli\u003eOver 20+ new recipes, including recognizing music genres and detecting objects in a scene\u003c\/li\u003e\n\u003cli\u003eCreate practical examples using TensorFlow Lite for Microcontrollers, Edge Impulse, and more\u003c\/li\u003e\n\u003cli\u003eExplore cutting-edge technologies, such as on-device training for updating models without data leaving the device\u003c\/li\u003e\n\u003c\/ul\u003eBook Description\u003cp\u003eDiscover the incredible world of tiny Machine Learning (tinyML) and create smart projects using real-world data sensors with the Arduino Nano 33 BLE Sense, Raspberry Pi Pico, and SparkFun RedBoard Artemis Nano.\u003c\/p\u003e\u003cp\u003eTinyML 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 TensorFlow and Edge Impulse.Expert tips will help you squeeze ML models into tight memory budgets and accelerate performance using CMSIS-DSP.\u003c\/p\u003e\u003cp\u003eThis 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 microTVM, including on a microNPU. This beginner-friendly and comprehensive book will help you stay up to date with the latest developments in the tinyML community and give you the knowledge to build unique projects with microcontrollers!\u003c\/p\u003eWhat you will learn\u003cul\u003e\n\u003cli\u003eUnderstand the microcontroller programming fundamentals\u003c\/li\u003e\n\u003cli\u003eWork with real-world sensors, such as the microphone, camera, and accelerometer\u003c\/li\u003e\n\u003cli\u003eImplement an app that responds to human voice or recognizes music genres\u003c\/li\u003e\n\u003cli\u003eLeverage transfer learning with FOMO and Keras\u003c\/li\u003e\n\u003cli\u003eLearn best practices on how to use the CMSIS-DSP library\u003c\/li\u003e\n\u003cli\u003eCreate a gesture-recognition app to build a remote control\u003c\/li\u003e\n\u003cli\u003eDesign a CIFAR-10 model for memory-constrained microcontrollers\u003c\/li\u003e\n\u003cli\u003eTrain a neural network on microcontrollers\u003c\/li\u003e\n\u003c\/ul\u003eWho this book is for\u003cp\u003eThis book is ideal for machine learning engineers or data scientists looking to build embedded\/edge ML applications and IoT developers who want to add machine learning capabilities to their devices. If you're an engineer, student, or hobbyist interested in exploring tinyML, then this book is your perfect companion.\u003c\/p\u003e\u003cp\u003eBasic familiarity with C\/C++ and Python programming is a prerequisite; however, no prior knowledge of microcontrollers is necessary to get started with this book.\u003c\/p\u003eTable of Contents\u003col\u003e\n\u003cli\u003eGetting Ready to Unlock ML on Microcontrollers\u003c\/li\u003e\n\u003cli\u003eUnleashing Your Creativity with Microcontrollers\u003c\/li\u003e\n\u003cli\u003eBuilding a Weather Station with TensorFlow Lite for Microcontrollers\u003c\/li\u003e\n\u003cli\u003eUsing Edge Impulse and the Arduino Nano to Control LEDs with Voice Commands\u003c\/li\u003e\n\u003cli\u003eRecognizing Music Genres with TensorFlow and the Raspberry Pi Pico - Part 1\u003c\/li\u003e\n\u003cli\u003eRecognizing Music Genres with TensorFlow and the Raspberry Pi Pico - Part 2\u003c\/li\u003e\n\u003cli\u003eDetecting Objects with Edge Impulse Using FOMO on the Raspberry Pi Pico\u003c\/li\u003e\n\u003cli\u003eClassifying Desk Objects with TensorFlow and the Arduino Nano\u003c\/li\u003e\n\u003cli\u003eBuilding a Gesture-Based Interface for YouTube Playback with Edge Impulse and the Raspberry Pi Pico\u003c\/li\u003e\n\u003c\/ol\u003e\u003cp\u003e(N.B. Please use the Look Inside option to see further chapters)\u003c\/p\u003e\u003cbr\u003e","brand":"Packt Publishing","offers":[{"title":"Default Title","offer_id":50523065483538,"sku":"9781837637362","price":40.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0831\/4771\/8930\/files\/img_143443ec-7ebe-4086-ba08-1a8d66b41586.jpg?v=1731134428","url":"https:\/\/surprise-castle.myshopify.com\/products\/tinyml-cookbook-second-edition-combine-machine-learning-with-microcontrollers-to-solve-real-world-problems-9781837637362","provider":"Surprise Castle","version":"1.0","type":"link"}