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TensorFlow Machine Learning Cookbook

You're reading from   TensorFlow Machine Learning Cookbook Over 60 recipes to build intelligent machine learning systems with the power of Python

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Product type Paperback
Published in Aug 2018
Publisher Packt
ISBN-13 9781789131680
Length 422 pages
Edition 2nd Edition
Languages
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Authors (2):
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Sujit Pal Sujit Pal
Author Profile Icon Sujit Pal
Sujit Pal
Nick McClure Nick McClure
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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 12. Other Books You May Enjoy

Implementing unit tests

Testing code results in faster prototyping, more efficient debugging, and faster changing, and makes it easier to share code. There are a number of simple ways to implement unit tests in TensorFlow, and we will cover them in this recipe.

Getting ready

When programming a TensorFlow model, it helps to have unit tests to check the functionality of the program. This helps us because when we want to make changes to a program unit, tests will make sure those changes do not break the model in unknown ways. In this recipe, we will create a simple CNN network that relies on the MNIST data. With it, we will implement three different types of unit test to illustrate how to write them in TensorFlow.

Note that Python...
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