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TensorFlow Machine Learning Cookbook

You're reading from   TensorFlow Machine Learning Cookbook Over 60 practical recipes to help you master Google's TensorFlow machine learning library

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Product type Paperback
Published in Feb 2017
Publisher Packt
ISBN-13 9781786462169
Length 370 pages
Edition 1st Edition
Languages
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Author (1):
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Nick McClure Nick McClure
Author Profile Icon Nick McClure
Nick McClure
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Toc

Table of Contents (13) Chapters Close

Preface 1. Getting Started with TensorFlow FREE CHAPTER 2. The TensorFlow Way 3. Linear Regression 4. Support Vector Machines 5. Nearest Neighbor Methods 6. Neural Networks 7. Natural Language Processing 8. Convolutional Neural Networks 9. Recurrent Neural Networks 10. Taking TensorFlow to Production 11. More with TensorFlow Index

Productionalizing TensorFlow – An Example


A good practice for productionalizing machine learning models is to separate the training and evaluation programs. Here, we illustrate an evaluation script expanded to include a unit test, model saving and loading, and evaluation.

Getting ready

For this recipe, we will show how to implement an evaluation script, using the above production criteria. The code actually consists of a training script and an evaluation script, but for this recipe, we will only show the evaluation script. As a reminder, both scripts can been seen in the online GitHub repository, https://github.com/nfmcclure/tensorflow_cookbook/.

For the example, we will implement the first RNN example from Chapter 9, Recurrent Neural Networks, which attempts to predict if a text message is spam or ham. We will assume the RNN model is trained and saved, along with the vocabulary.

How to do it…

  1. We start by loading the necessary libraries and declaring the TensorFlow application flags:

    import os...
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