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Machine Learning with TensorFlow, 2nd Edition
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  • Title Machine Learning with TensorFlow, 2nd Edition
  • Author(s): Mattmann A. Chris
  • Publisher: Manning; 2nd edition (February 2, 2021)
  • Permission: Free to read entire book online by the publisher (Manning), limited time every day.
  • Paperback: 456 pages
  • eBook: HTML
  • Language: English
  • ISBN-10: 1617297712
  • ISBN-13: 978-1617297717
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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
  • Chris Mattmann is the Division Manager of the Artificial Intelligence, Analytics, and Innovation Organization at NASA Jet Propulsion Lab. The first edition of this book was written by Nishant Shukla with Kenneth Fricklas.
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