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Practical Machine Learning in JavaScript

TensorFlow.js for Web Developers

Apress

Authors:

  • Move from basic web development into the field of machine learning

  • Incorporate the ethics of AI into your development considerations

  • Harness your existing skills with JavaScript to learn a new approach to development

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  • Read on any device
  • Instant download
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Softcover Book USD 44.99
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Table of contents (7 chapters)

  1. Front Matter

    Pages i-xvi
  2. The basics of machine learning

    • Charlie Gerard
    Pages 1-24
  3. TensorFlow.js

    • Charlie Gerard
    Pages 25-43
  4. Building an image classifier

    • Charlie Gerard
    Pages 45-66
  5. Text classification and sentiment analysis

    • Charlie Gerard
    Pages 67-134
  6. Experimenting with inputs

    • Charlie Gerard
    Pages 135-286
  7. Machine learning in production

    • Charlie Gerard
    Pages 287-303
  8. Bias in machine learning

    • Charlie Gerard
    Pages 305-316
  9. Back Matter

    Pages 317-323

About this book

Build machine learning web applications without having to learn a new language. This book will help you develop basic knowledge of machine learning concepts and applications. 

You’ll learn not only theory, but also dive into code samples and example projects with TensorFlow.js. Using these skills and your knowledge as a web developer, you’ll add a whole new field of development to your tool set. This will give you a more concrete understanding of the possibilities offered by machine learning. Discover how ML will impact the future of not just programming in general, but web development specifically. 

Machine learning is currently one of the most exciting technology fields with the potential to impact industries from health to home automation to retail, and even art. Google has now introduced TensorFlow.js—an iteration of TensorFlow aimed directly at web developers. Practical Machine Learning in JavaScript will help you stay relevant in the tech industry with new tools, trends, and best practices.

What You'll Learn

  • Use the JavaScript framework for ML
  • Build machine learning applications for the web
  • Develop dynamic and intelligent web content

Who This Book Is For

Web developers and who want a hands-on introduction to machine learning in JavaScript. A working knowledge of the JavaScript language is recommended. 




Authors and Affiliations

  • Les Clayes sous bois, France

    Charlie Gerard

About the author

Charlie Gerard is a Senior front-end developer at Netlify, a Google Developer Expert in Web Technologies, and a Mozilla Tech Speaker. She is passionate about exploring the possibilities of the web and spends her personal time building interactive prototypes using hardware, creative coding, and machine learning. She has been diving into ML in JavaScript for over a year and built a variety of projects. She’s excited to share what she’s learned and help more developers get started.

Bibliographic Information

  • Book Title: Practical Machine Learning in JavaScript

  • Book Subtitle: TensorFlow.js for Web Developers

  • Authors: Charlie Gerard

  • DOI: https://doi.org/10.1007/978-1-4842-6418-8

  • Publisher: Apress Berkeley, CA

  • eBook Packages: Professional and Applied Computing, Professional and Applied Computing (R0), Apress Access Books

  • Copyright Information: Charlie Gerard 2021

  • Softcover ISBN: 978-1-4842-6417-1Published: 17 November 2020

  • eBook ISBN: 978-1-4842-6418-8Published: 16 November 2020

  • Edition Number: 1

  • Number of Pages: XVI, 323

  • Number of Illustrations: 110 b/w illustrations

  • Topics: Artificial Intelligence

Buy it now

Buying options

eBook USD 34.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 44.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access