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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 a simple CNN

In this recipe, we will develop a four-layer convolutional neural network to improve upon our accuracy in predicting MNIST digits. The first two convolution layers will each be composed of convolution-ReLU-Max Pool operations, and the final two layers will be fully connected layers.

Getting ready

To access the MNIST data, TensorFlow has an examples.tutorials package that has great dataset-loading functionalities. After we load the data, we will set up our model variables, create the model, train the model in batches, and then visualize loss, accuracy, and some sample digits.

How to do it...

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