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

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Practical Machine Learning in JavaScript: Tensorflow.Js for Web Developers, (Paperback)
Author: Apress
ISBN: 9781484264171
Format: Paperback
Publication Date: 2020-11-17
Page Count: 323

Specs

Book format
Paperback
Fiction/nonfiction
Non-Fiction
Genre
Computing & Internet
Pub date
2020-11-17
Pages
323
Subgenre
Artificial Intelligence

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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.

Practical Machine Learning in JavaScript: Tensorflow.Js for Web Developers, (Paperback)
Author: Apress
ISBN: 9781484264171
Format: Paperback
Publication Date: 2020-11-17
Page Count: 323

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Specifications

Book format

Paperback

Fiction/nonfiction

Non-Fiction

Genre

Computing & Internet

Pub date

2020-11-17

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