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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
 ISBN10: 1617297712
 ISBN13: 9781617297717
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Book Description
TensorFlow, Google's library for largescale machine learning, simplifies oftencomplex 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 machinelearning concepts plus handson 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 deeplearning concepts like autoencoders, recurrent neural networks, and reinforcement learning.
Digest this book and you will be ready to use TensorFlow for machinelearning and deeplearning applications of your own.
Updated with new code, new projects, and new chapters, Second Edition gives readers a solid foundation in machinelearning concepts and the TensorFlow library.
 Matching your tasks to the right machinelearning and deeplearning approaches
 Visualizing algorithms with TensorBoard
 Understanding and using neural networks
 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.
 Machine Learning
 Neural Networks and Deep Learning
 Python Programming
 Artificial Intelligence
 Data Science

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