Practical Machine Learning in JavaScript by Charlie Gerard is an essential guide for web developers looking to integrate machine learning into their web applications using JavaScript and TensorFlow.js. This book offers step-by-step instructions and real-world examples to help you bring intelligent features to your websites.

Book Summary

  • Title: Practical Machine Learning in JavaScript: TensorFlow.js for Web Developers
  • Author: Charlie Gerard
  • Publication Year: 2020
  • Publisher: Apress
  • Language: English
  • Pages: 340
  • ISBN: 978-1484264171

What You’ll Learn

In Practical Machine Learning in JavaScript, Charlie Gerard walks you through the essential steps of applying machine learning models directly within web environments. You’ll start by understanding the core concepts of machine learning and how they can be adapted for use in JavaScript. The book covers setting up TensorFlow.js and building machine learning models from scratch.

You’ll also explore a variety of machine learning algorithms such as linear regression, classification, clustering, and neural networks. Each chapter provides clear instructions on how to implement these algorithms in JavaScript, enabling you to put your skills to use right away. Additionally, the book highlights key topics like data preparation, visualization, and how to integrate machine learning models into web applications.

Who Is This Book For?

This guide is perfect for:

  • Web developers seeking to incorporate machine learning into their websites.
  • Data engineers wanting to apply machine learning in a web context.
  • Students and instructors looking for a solid educational resource for courses on web development and machine learning.
  • IT professionals and enthusiasts eager to learn about machine learning and its practical applications.

What Sets This Book Apart?

Practical Machine Learning in JavaScript stands out for its hands-on approach, offering practical, easy-to-follow examples and code that can be applied directly in your projects. You’ll learn how to integrate machine learning models into websites, enhance user experiences, and explore new opportunities that machine learning presents for web development.

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. Her passion lies in pushing the boundaries of the web, and she frequently experiments with creative coding, hardware, and machine learning. With over a year of experience in machine learning using JavaScript, she has created numerous projects and is highly regarded in the developer community.

If you’re looking to level up your web development skills with machine learning, Practical Machine Learning in JavaScript is a must-read. For more guides and resources on programming and web development, visit ThinkJava.net, where we share insights and tools to help you succeed in your coding journey.

Categorized in:

JavaScript, Machine Learning,

Last Update: October 2, 2024

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