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Machine Learning with TensorFlow
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  • Title Machine Learning with TensorFlow
  • Author(s) Nishant Shukla, Mattmann A. Chris
  • Publisher: Manning; 1 edition (2018), 2nd edition (February 2, 2021)
  • Permission: Free to read entire book online by the publisher (Manning), 5 minutes every day.
  • Paperback 227 pages (1 edition); 456 pages (2nd edition)
  • eBook HTML
  • Language: English
  • ISBN-10: 1617293873 (1 edition), 1617297712 (2nd edition)
  • ISBN-13: 978-1617293870 (1 edition), 978-1617297717 (2nd edition)
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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.

Updated with new code, new projects, and new chapters, Second Edition gives readers a solid foundation in machine-learning concepts and the TensorFlow library.

  • 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.
  • Chris Mattmann is the Deputy Chief Technology and Innovation Officer at NASA Jet Propulsion Lab, where he has been recognised as JPL's first Principal Scientist in the area of Data Science. Chris has applied TensorFlow to challenges he’s faced at NASA, including building an implementation of Google’s Show & Tell algorithm for image captioning using TensorFlow.
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