Deep Learning with JavaScript you own this product

Neural networks in TensorFlow.js
Shanqing Cai, Stanley Bileschi, Eric D. Nielsen with Francois Chollet
Foreword by Nikhil Thorat and Daniel Smilkov
  • January 2020
  • ISBN 9781617296178
  • 560 pages
Included with a Manning Online subscription
  • printed in black & white
  • Available translations: Complex Chinese, Korean, Russian, Simplified Chinese
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Look inside
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. Deep Learning with JavaScript shows developers how they can bring DL 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.

about the technology

Running deep learning applications in the browser or on Node-based backends opens up exciting possibilities for smart web applications. With the TensorFlow.js library, you build and train deep learning models with JavaScript. Offering uncompromising production-quality scalability, modularity, and responsiveness, TensorFlow.js really shines for its portability. Its models run anywhere JavaScript runs, pushing ML farther up the application stack.

about the book

In Deep Learning with JavaScript, you’ll learn to use TensorFlow.js to build deep learning models that run directly in the browser. This fast-paced book, written by Google engineers, is practical, engaging, and easy to follow. 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.

what's inside

  • 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 reader

For JavaScript programmers interested in deep learning.

about the author

Shanging Cai, Stanley Bileschi and Eric D. Nielsen are software engineers with experience on the Google Brain team, and were crucial to the development of the high-level API of TensorFlow.js. This book is based in part on the classic, Deep Learning with Python by François Chollet.

This book should serve as the authoritative source for readers who want to learn ML and use JavaScript as their main language.

From the Foreword by Nikhil Thorat and Daniel Smilkov, TensorFlow.js

Packed with a wealth of information about deep learning, this eminently readable book makes a very strong case for using JavaScript for machine learning.

George Thomas, R&D, Manhattan Associates

This book is your guide through the world of deep learning, chauffeured by the very best in their field. You will be amazed at how much it is possible to do in a browser nowadays.

Edin Kapić, iSolutions

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