"Practical Machine Learning in JavaScript" by Charlie Gerard is considered a key guide for web developers aiming to master machine learning using JavaScript and TensorFlow.js. This edition offers step-by-step instructions and practical examples to help you integrate machine learning models directly into web applications.
You will gain valuable knowledge on how to apply modern technologies to create intelligent and interactive websites. Download "Practical Machine Learning in JavaScript: TensorFlow.js for Web Developers" in PDF today to start enhancing your skills.
Who Should Read This Edition?
- Web Developers: The manual will help you master machine learning and integrate it into your web applications.
- Data Engineers: You will gain knowledge on applying machine learning in a web environment, expanding your professional skills.
- Students and Instructors: The book will be an excellent educational resource for courses on machine learning and web development.
- IT Professionals and Enthusiasts: The edition is useful for anyone interested in learning about machine learning and its practical applications.
What’s Inside the Book "Practical Machine Learning in JavaScript: TensorFlow.js for Web Developers"?
It contains detailed material covering all the necessary aspects of mastering machine learning using JS and TensorFlow.js. The author begins with an introduction to the basic concepts of machine learning, explaining how they apply to web development. You will learn how to install and set up TensorFlow.js and use it to create machine learning models.
The book then covers various machine learning algorithms, such as linear regression, classification, clustering, and neural networks. The author provides step-by-step instructions for implementing these algorithms in JavaScript, allowing you to immediately apply the acquired knowledge in practice. The book also emphasizes data processing, preparation, and visualization, which are essential parts of the machine learning process.
Separate chapters are dedicated to integrating machine learning models into web applications. You will get useful tips and examples to help you deploy models on a website and enhance the user experience. The book concludes with a discussion of advanced topics and new opportunities that machine learning offers in the web environment.
More About the Author of the Book
FAQ for "Practical Machine Learning in JavaScript: TensorFlow.js for Web Developers"
What main topics does this edition cover?
It covers the basics of machine learning, setting up and using TensorFlow.js, implementing various machine learning algorithms in JS, data processing and visualization, and integrating models into web applications.
What skills can I develop by studying "Practical Machine Learning in JavaScript"?
You will develop skills in using TensorFlow.js, creating and training machine learning models, integrating them into web applications, and analyzing and visualizing data.
What JavaScript libraries are discussed in the book?
The edition thoroughly examines TensorFlow.js and other useful libraries for data analysis and machine learning widely used in web development.
Is the textbook suitable for absolute beginners in working with TensorFlow.js?
Yes, it is suitable for beginners. The author starts with basic concepts and gradually moves on to more complex topics, making it easy to understand the material and apply the acquired knowledge in practice.
How does the book help with the practical application of knowledge?
It includes numerous practical examples and tasks that help you immediately apply the acquired knowledge in practice. You will be able to create real projects and see the results of your work.
Information
| Author: | Charlie Gerard | Language: | English |
| Publisher: | Apress | ISBN-13: | 978-1484264171 |
| Publication Date: | November 17, 2020 | ISBN-10: | 1484264177 |
| Print Length: | 340 pages |
Free download "Practical Machine Learning in JavaScript: TensorFlow.js for Web Developers" by Charlie Gerard in PDF
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