Isbn: 9798197978127 - the tinyml developer’s guide: design, train, and deploy machine learning models on resource-constrained devices (5 resultados)

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  • Idioma: Inglés

    Editorial: Independently published, 2026

    9798197978127

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    Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US

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    EUR 31,18

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    PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

  • Idioma: Inglés

    Editorial: Independently published, 2026

    9798197978127

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    Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK

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    PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

  • Idioma: Inglés

    Editorial: Independently Published Mai 2026, 2026

    9798197978127

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    EUR 39,86

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    Taschenbuch. Condición: Neu. Neuware - What if your devices could do more than collect data-what if they could actually understand it What if a tiny microcontroller could recognize voice commands, detect motion, or respond intelligently in real time without relying on the cloud The TinyML Developer's Guide by Ellis Jasper Harry, PhD introduces you to the world of TinyML and edge AI, where machine learning models run directly on small, low-power devices.This practical guide walks you step by step through designing, training, optimizing, and deploying machine learning models on embedded systems with limited memory and compute resources.Whether you are new to machine learning, embedded systems, or edge AI-or already experimenting with microcontrollers and intelligent devices-this book provides clear explanations and real-world examples to help you build practical TinyML applications.Inside, you will learn how to: - Convert raw sensor data into meaningful features- Train lightweight machine learning models for microcontrollers- Optimize models for speed, memory usage, and energy efficiency- Deploy TinyML applications for voice recognition, motion detection, and smart sensing- Build complete edge AI systems that work reliably in real-world environments- Understand how machine learning operates directly on embedded hardwareThis book focuses on practical implementation rather than abstract theory, helping you move from concepts to working intelligent systems.You will also explore the growing future of edge AI-where devices operate faster, protect privacy, and function independently without constant internet connectivity.If you are ready to build smarter embedded systems and understand how machine learning works on tiny devices, this guide is your starting point.Begin building intelligent edge devices with TinyML today.And if this book helps you learn, build, or better understand TinyML development, consider leaving a review to help other developers discover it as well.…

  • Idioma: Inglés

    Editorial: Independently published, 2026

    9798197978127

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    Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books

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    Condición: Nuevo

    EUR 26,67

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    Cantidad disponible: Más de 20 disponibles

    Condición: New. Print on Demand.

  • Idioma: Inglés

    Editorial: Independently Published, 2026

    9798197978127

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    Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail

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    Condición: Nuevo

    EUR 30,97

    Envío por EUR 43,65 
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    Cantidad disponible: 1 disponible

    Paperback. Condición: new. Paperback. What if your devices could do more than collect data-what if they could actually understand it?What if a tiny microcontroller could recognize voice commands, detect motion, or respond intelligently in real time without relying on the cloud?The TinyML Developer's Guide by Ellis Jasper Harry, PhD introduces you to the world of TinyML and edge AI, where machine learning models run directly on small, low-power devices.This practical guide walks you step by step through designing, training, optimizing, and deploying machine learning models on embedded systems with limited memory and compute resources.Whether you are new to machine learning, embedded systems, or edge AI-or already experimenting with microcontrollers and intelligent devices-this book provides clear explanations and real-world examples to help you build practical TinyML applications.Inside, you will learn how to: Convert raw sensor data into meaningful featuresTrain lightweight machine learning models for microcontrollersOptimize models for speed, memory usage, and energy efficiencyDeploy TinyML applications for voice recognition, motion detection, and smart sensingBuild complete edge AI systems that work reliably in real-world environmentsUnderstand how machine learning operates directly on embedded hardwareThis book focuses on practical implementation rather than abstract theory, helping you move from concepts to working intelligent systems.You will also explore the growing future of edge AI-where devices operate faster, protect privacy, and function independently without constant internet connectivity.If you are ready to build smarter embedded systems and understand how machine learning works on tiny devices, this guide is your starting point.Begin building intelligent edge devices with TinyML today.And if this book helps you learn, build, or better understand TinyML development, consider leaving a review to help other developers discover it as well. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…