Overview
- 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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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.
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Table of contents (7 chapters)
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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, Apress Access Books, Professional and Applied Computing (R0)
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