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Machine Learning with TensorFlow 1.x

You're reading from   Machine Learning with TensorFlow 1.x Second generation machine learning with Google's brainchild - TensorFlow 1.x

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Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781786462961
Length 304 pages
Edition 1st Edition
Languages
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Authors (3):
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 Hua Hua
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Hua
 Ahmed Ahmed
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Ahmed
 Ul Azeem Ul Azeem
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Ul Azeem
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Toc

Table of Contents (19) Chapters Close

Title Page
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Getting Started with TensorFlow FREE CHAPTER 2. Your First Classifier 3. The TensorFlow Toolbox 4. Cats and Dogs 5. Sequence to Sequence Models-Parlez-vous Français? 6. Finding Meaning 7. Making Money with Machine Learning 8. The Doctor Will See You Now 9. Cruise Control - Automation 10. Go Live and Go Big 11. Going Further - 21 Problems 12. Advanced Installation

Additional setup


Additional setup is required to include libraries required for text processing. Take a look at the following points:

  1. First is Bazel. On Ubuntu, you will need to follow the official tutorial on this link to install Bazel. https://docs.bazel.build/versions/master/install-ubuntu.html. On macOS, you can use HomeBrew to install bazel as follows:
$ brew install bazel
  1. Then, we will install swig, which will allow us to wrap C/C++ functions to allow calls in Python. On Ubuntu, you can install it using:
      $ sudo apt-get install swig

On Mac OS, we will also install it using brew, as follows:

$ brew install swig
  1. Next, we'll install the protocol buffer support, which will allow us to store and retrieve serialized data in a more efficient manner than with XML. We specifically need version 3.3.0 to install it as follows:
$ pip install -U protobuf==3.3.0
  1. Our text classification will be represented as trees, so we'll need a library to display trees on the command line. We will install it as follows...
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