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Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning

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Practical Machine Learning in JavaScript - TensorFlow.js for Web Developers (Paperback, 1st ed.) Loot Price: R1,105
Discovery Miles 11 050
You Save: R303 (22%)
Practical Machine Learning in JavaScript - TensorFlow.js for Web Developers (Paperback, 1st ed.): Charlie Gerard

Practical Machine Learning in JavaScript - TensorFlow.js for Web Developers (Paperback, 1st ed.)

Charlie Gerard

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List price R1,408 Loot Price R1,105 Discovery Miles 11 050 | Repayment Terms: R104 pm x 12* You Save R303 (22%)

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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.

General

Imprint: Apress
Country of origin: United States
Release date: November 2020
First published: 2021
Authors: Charlie Gerard
Dimensions: 235 x 155 x 21mm (L x W x T)
Format: Paperback
Pages: 323
Edition: 1st ed.
ISBN-13: 978-1-4842-6417-1
Categories: Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN: 1-4842-6417-7
Barcode: 9781484264171

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