TinyML Cookbook - Second Edition: Combine machine learning with microcontrollers to solve real-world problems, (Paperback)
Expert tips will help you squeeze ML models into tight memory budgets and accelerate performance using CMSIS-DSP.
TinyML Cookbook - Second Edition: Combine machine learning with microcontrollers to solve real-world problems, (Paperback)
Artigo n.º: 86451434

TinyML Cookbook - Second Edition: Combine machine learning with microcontrollers to solve real-world problems, (Paperback)

Artigo n.º: 86451434

AOA 54734

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Expert tips will help you squeeze ML models into tight memory budgets and accelerate performance using CMSIS-DSP.
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O que se Destaca

Hands-On Recipes
Offers practical, step-by-step guides to implement machine learning on microcontrollers, empowering readers to tackle real-world challenges effectively and efficiently.
Updated Content
The second edition includes the latest advancements in TinyML, ensuring that readers are equipped with current knowledge and techniques in the rapidly evolving field of machine learning.
Broad Applicability
Designed for diverse audiences, from hobbyists to professionals, making it accessible for anyone interested in integrating machine learning into everyday applications using microcontrollers.

Detalhes do produto

Shop TinyML Cookbook - Second Edition: Combine machine learning with microcontrollers to solve real-world problems, (Paperback) online at a best price in Angola. 5245154042
  • 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. 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.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 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 you're 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.Table of ContentsGetting Ready to Unlock ML on MicrocontrollersUnleashing Your Creativity with MicrocontrollersBuilding a Weather Station with TensorFlow Lite for Microcontrollers&am
Book formatPaperback
Edition2nd Edition
Skill levelBeginner
Pages664
LanguageEnglish
BrandGian Marco Iodice
AuthorPackt Publishing
SubgenreMachine Theory
GenreComputing & Internet
Bisac subject headingComputers
Series titleNo Series
Dimensions7.50 x 1.33 x 9.25 in (19.1 x 3.4 x 23.5 cm)
Age groupAdult
Retail packagingSingle Piece
Original languagesEnglish

Quem Deverá Comprar?

Suitable For
  • Students and Learners

    Ideal for students studying machine learning or embedded systems, facilitating hands-on projects and practical applications.

  • Engineers and Developers

    Great for engineers developing IoT solutions, leveraging microcontrollers and TinyML for innovative product designs.

  • Hobbyists and Makers

    Perfect for hobbyists looking to integrate machine learning in DIY electronics projects with accessible and easy-to-follow recipes.

Not Suitable For
  • Beginners in Programming

    Not suitable for those with no programming knowledge, as the concepts may be too advanced without prior experience.

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Gian Marco Iodice Microprocessors Books Editorial Review

The TinyML Cookbook - Second Edition is a comprehensive guide that expertly blends machine learning principles with microcontroller applications, tailored specifically for beginners to navigate the evolving landscape of technology. With 664 pages of rich content authored by Gian Marco Iodice from Packt Publishing, this paperback edition provides practical insights and hands-on projects designed to address real-world problems. Readers will appreciate its clear explanations and the focus on practical skills development which is essential for understanding machine theory in computing and the internet realm. Whether you're a novice or someone looking to refresh your skills, this cookbook serves as a valuable resource.

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Prós

  • Ideal for beginners in machine learning
  • Practical examples for real-world applications
  • Comprehensive 664-page guide
  • Written by experienced authors
  • Focuses on microcontroller integration

Contras

  • May be too basic for advanced learners

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