Description: TinyML Cookbook by Gian Marco Iodice With over 70 project-based recipes, the TinyML Cookbook is a practical guide that will help you to get the most out of your microcontrollers. FORMAT Paperback CONDITION Brand New Publisher Description Over 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 learningPurchase of the print or Kindle book includes a free eBook in PDF format.Key FeaturesOver 20+ new recipes, including recognizing music genres and detecting objects in a sceneCreate practical examples using TensorFlow Lite for Microcontrollers, Edge Impulse, and moreExplore cutting-edge technologies, such as on-device training for updating models without data leaving the deviceBook DescriptionDiscover 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.TinyML 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. Youll 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.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, youll 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!What you will learnUnderstand the microcontroller programming fundamentalsWork with real-world sensors, such as the microphone, camera, and accelerometerImplement an app that responds to human voice or recognizes music genresLeverage transfer learning with FOMO and KerasLearn best practices on how to use the CMSIS-DSP libraryCreate a gesture-recognition app to build a remote controlDesign a CIFAR-10 model for memory-constrained microcontrollersTrain a neural network on microcontrollersWho this book is forThis 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 youre an engineer, student, or hobbyist interested in exploring tinyML, 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. Author Biography Gian Marco Iodice is team and tech lead in the Machine Learning Group at Arm, who co-created the Arm Compute Library in 2017. The Arm Compute Library is currently the most performant library for ML on Arm, and its deployed on billions of devices worldwide – from servers to smartphones.Gian Marco holds an MSc degree, with honors, in electronic engineering from the University of Pisa (Italy) and has several years of experience developing ML and computer vision algorithms on edge devices. Now, hes leading the ML performance optimization on Arm Mali GPUs.In 2020, Gian Marco cofounded the TinyML UK meetup group to encourage knowledge-sharing, educate, and inspire the next generation of ML developers on tiny and power-efficient devices. Table of Contents Table of ContentsGetting Ready to Unlock ML on MicrocontrollersUnleashing Your Creativity with MicrocontrollersBuilding a Weather Station with TensorFlow Lite for MicrocontrollersUsing Edge Impulse and the Arduino Nano to Control LEDs with Voice CommandsRecognizing Music Genres with TensorFlow and the Raspberry Pi Pico – Part 1Recognizing Music Genres with TensorFlow and the Raspberry Pi Pico – Part 2Detecting Objects with Edge Impulse Using FOMO on the Raspberry Pi PicoClassifying Desk Objects with TensorFlow and the Arduino NanoBuilding a Gesture-Based Interface for YouTube Playback with Edge Impulse and the Raspberry Pi PicoDeploying a CIFAR-10 Model for Memory-Constrained Devices with the Zephyr OS on QEMURunning ML Models on Arduino and the Arm Ethos-U55 microNPU Using Apache TVMEnabling Compelling tinyML Solutions with On-Device Learning and scikit-learn on the Arduino Nano and RaspberryPi Pico Details ISBN1837637369 Author Gian Marco Iodice Publisher Packt Publishing Limited Edition Description 2nd Revised edition Year 2023 Edition 2nd ISBN-13 9781837637362 Format Paperback Imprint Packt Publishing Limited Subtitle Combine machine learning with microcontrollers to solve real-world problems Place of Publication Birmingham Country of Publication United Kingdom Replaces 9781801814973 DEWEY 006.31 Audience Professional & Vocational Pages 664 Publication Date 2023-11-29 UK Release Date 2023-11-29 We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:159791288;
Price: 96.51 AUD
Location: Melbourne
End Time: 2024-11-07T05:03:05.000Z
Shipping Cost: 24.04 AUD
Product Images
Item Specifics
Restocking fee: No
Return shipping will be paid by: Buyer
Returns Accepted: Returns Accepted
Item must be returned within: 30 Days
Format: Paperback
ISBN-13: 9781837637362
Author: Gian Marco Iodice
Type: Does not apply
Book Title: TinyML Cookbook
Language: Does not apply
