Deep Learning with JavaScript: Neural Networks in TensorFlow.js (Shanqing Cai, et al)

 
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Deep Learning with JavaScript: Neural Networks in TensorFlow.js (Shanqing Cai, et al)

The domains of computer vision, image processing, and natural language applications have all been revolutionized by deep learning. TensorFlow.js has made it possible for JavaScript developers to create deep-learning applications without using Python or R.

This book demonstrates to programmers how to integrate deep learning technology into websites. This new book offers exciting use examples and in-depth instructions for deep learning apps in JavaScript in your browser or on Node.js. It was written by the primary creators of the TensorFlow framework.

You will study the fundamentals of deep learning and explore more complex ideas, such as retraining existing models for transfer learning and picture production. These examples span a variety of fields, including text analysis, speech processing, image recognition, and self-learning gaming AI.

  • Image and language processing in the browser
  • Tuning ML models with client-side data
  • Text and image creation with generative deep learning
  • Source code samples to test and modify

Ebook Details

About the Authors
  • One of the creators of TensorFlow, a well-known open-source framework for deep learning and artificial intelligence, is Shanqing Cai.
  • The Google TensorFlow Usability team, which created the TensorFlow Layers API, has Stan Bileschi as its technical lead.
  • On the Google Brain team, Eric Nielsen is a senior software engineer.
Published
Published Date / Year
1 edition (January 14, 2020)
Permission
Free to read entire book online by the publisher (Manning), with limited time every day.
Hardcover
350 pages
eBook Format
HTML
Language
English
ISBN-10
1617296171
ISBN-13
978-1617296178

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