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Deep Learning with JavaScript: Neural Networks in TensorFlow.js
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  • Title: Deep Learning with JavaScript: Neural Networks in TensorFlow.js
  • Author(s) Shanqing Cai, Stanley Bileschi, Eric D. Nielsen with Francois Chollet
  • Publisher: Manning Publications; 1 edition (January 14, 2020)
  • Permission: Free to read entire book online by the publisher (Manning), with limited time every day.
  • Hardcover/Paperback: 350 pages
  • eBook: HTML
  • Language: English
  • ISBN-10/ASIN: 1617296171
  • ISBN-13: 978-1617296178
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Book Description

Deep learning has transformed the fields of computer vision, image processing, and natural language applications. Thanks to TensorFlow.js, now JavaScript developers can build deep learning apps without relying on Python or R.

This book shows developers how they can bring Deep learning technology to the web. Written by the main authors of the TensorFlow library, this new book provides fascinating use cases and in-depth instruction for deep learning apps in JavaScript in your browser or on Node.js.

Through diverse examples featuring text analysis, speech processing, image recognition, and self-learning game AI, you'll master all the basics of deep learning and explore advanced concepts, like retraining existing models for transfer learning and image generation.

  • 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
About the Authors
  • Shanqing Cai is one of the developers of TensorFlow, a popular open-source framework for deep learning and artificial intelligence.
  • Stan Bileschi is the technical lead for Google's TensorFlow Usability team, which built the TensorFlow Layers API.
  • Eric Nielsen is a senior software engineer on the Google Brain team.
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