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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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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

Implementing DeepDream


Another usage of trained CNNs is exploiting the fact that some of the intermediate nodes detect features of labels (e.g. a cat ear or a feather of a bird). Using this fact, we can find ways to transform any image to reflect those node features of any node we choose. For this recipe, we will go through the DeepDream tutorial on TensorFlow's website. But for this recipe, we will go through the essential parts in much more detail. The hope is that we can prepare the reader to use the DeepDream algorithm for exploration of CNNs and features created in such CNNs.

Getting ready

TensorFlow's official tutorials show how to implement DeepDream through a script (refer to the first bullet point of the See also section). The purpose of this recipe is to go through the script they provide and explain each line. While the tutorial is great, there are some parts that are skippable and some parts that could use more explanation. We hope to provide a more detailed line-by-line explanation...

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