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Shukla -- Machine Learning with TensorFlow -- 2017 pdf torrent |
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0A013BA961F248CB44761C6DF29D60A90B0728EA |
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5.30 MB |
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| Torrent added: | 2024-09-10 08:17:42 |
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Torrent Description
Machine Learning with TensorFlow
Authors: Nishant Shukla
Genres
Programming
Artificial Intelligence
Technical
Computer Science
Computers
Description:
Summary
Machine Learning with TensorFlow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding TensorFlow with Python.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
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 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
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.
Table of Contents
Goodreads page:
https://www.goodreads.com/book/show/31338523-machine-learning-with-tensorflow
Please note that this description is auto-generated by a bot, if you find the description incorrect then please report in the comments. Description will be edited accordingly afterwards.
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