Practical Machine Learning in JavaScript: Tensorflow.Js for Web Developers (Paperback)

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Description


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 already honed skills as a web developer, you'll add a whole new field of development to your skill 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. Get started in machine learning with web technologies.

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.


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.


Product Details
ISBN: 9781484264171
ISBN-10: 1484264177
Publisher: Apress
Publication Date: December 1st, 2020
Pages: 323
Language: English