Practical Machine Learning in JavaScript
Author | : Charlie Gerard |
Publisher | : Apress |
Total Pages | : 323 |
Release | : 2020-11-17 |
ISBN-13 | : 1484264177 |
ISBN-10 | : 9781484264171 |
Rating | : 4/5 (71 Downloads) |
Download or read book Practical Machine Learning in JavaScript written by Charlie Gerard and published by Apress. This book was released on 2020-11-17 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.