Machine Learning with TensorFlow

Nishant Shukla
with Kenneth Fricklas
  • January 2018
  • ISBN 9781617293870
  • 272 pages
  • printed in black & white

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A great guide to machine learning. It helped launch my third career!

William Wheeler, TEKsystems
Look inside

Machine Learning with TensorFlow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding TensorFlow with Python.

about the technology

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.

about the book

Machine Learning with TensorFlow 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.

what's inside

  • Matching your tasks to the right machine-learning and deep-learning approaches
  • Visualizing algorithms with TensorBoard
  • Understanding and using neural networks

about the reader

Written for developers experienced with Python and algebraic concepts like vectors and matrices.

about the author

Author Nishant Shukla is a computer vision researcher focused on applying machine-learning techniques in robotics.

Senior technical editor, Kenneth Fricklas, is a seasoned developer, author, and machine-learning practitioner.

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The many examples provide excellent hands-on experience.

Mikael Dautrey, ISITIX

Helped me to jump-start working with TensorFlow.

Ursin Stauss, Swiss Post

Learn how to use TensorFlow to power your machine-learning projects with this fast-paced yet unintimidating book!

Arthur Zubarev, SERMO
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