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Machine Learning with TensorFlow
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  • Title Machine Learning with TensorFlow
  • Author(s) Nishant Shukla
  • Publisher: Manning Publications; 1 edition (February 12, 2018)
  • License(s): Free to read online (entire book) by the publisher.
  • Paperback 227 pages
  • eBook HTML
  • Language: English
  • ISBN-10: 1617293873
  • ISBN-13: 978-1617293870
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Book Description

TensorFlow, Google's library for large-scale machine learning, simplifies often-complex computations by representing them as graphs and efficiently mapping parts of the graphs to machines in a cluster or to the processors of a single machine.

This book gives readers a solid foundation in machine-learning concepts plus hands-on experience coding TensorFlow with Python. You'll learn the basics by working with classic prediction, classification, and clustering algorithms. Then, you'll move on to the money chapters: exploration of deep-learning concepts like autoencoders, recurrent neural networks, and reinforcement learning. Digest this book and you will be ready to use TensorFlow for machine-learning and deep-learning applications of your own.

  • Matching your tasks to the right machine-learning and deep-learning approaches
  • Visualizing algorithms with TensorBoard
  • Understanding and using neural networks
About the Authors
  • Nishant Shukla is a computer vision researcher at UCLA, focusing on machine learning techniques with robotics. He has been a developer for Microsoft, Facebook, and Foursquare, and a machine learning engineer for SpaceX, as well as the author of the Haskell Data Analysis Cookbook.
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