Deep Learning with Javascript: Example-Based Approach

By Kenwright

Deep Learning with Javascript provides a beginners guide to getting started with neural networks. Through a hands-on approach the book provides a wide-range of interactive examples that the user is able to customize and expand to help them understand the concepts in a real-world sense. Using example-based learning and projects. The book has been formatted and designed with sample listings and support material, so whether or not you are currently an expert in Javascript and neural network development, actively working with an existing framework, or completely in the dark about this mysterious topic, this book has something for you. If you’re an experienced developer, you’ll find this book a light refresher to the subject, and if you’re deciding whether or not to delve into web-based games, this book may help you make that significant decision. The book introduces core mathematic fundamentals in addition to projects and exercises such as feature detection, inverse kinematics, text extaction from handwritten sources and much more. The text is organised to guide the reader through the exciting topic of deep learning from a ground-up hands-on perspective. Organized around the browser-based language (Javascript) in combination with popular open source libraries (Synaptic), the book includes numerous simplified practical examples in the body of the text as well as technical explanations on limitations and engineering workarounds.

Pages: 166
Publication: 29 June 2020
Language: English
ISBN: 9798660010767

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Deep Learning with Javascript: Example-Based Approach offers a comprehensive and in-depth guide that walks you through the concepts, applications, and best practices. With a strong focus on hands-on examples and real-world relevance, it empowers you to not just learn the theory but to apply it in meaningful ways across graphics, compute, and more.

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