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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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Nick McClure Nick McClure
Author Profile Icon Nick McClure
Nick McClure
Sujit Pal Sujit Pal
Author Profile Icon Sujit Pal
Sujit Pal
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Toc

Table of Contents (19) Chapters Close

Title Page
Copyright and Credits
Dedication
Packt Upsell
Contributors
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 1. Other Books You May Enjoy Index

Implementing DeepDream


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

Getting ready

TensorFlow's official tutorials show how to implement DeepDream through a script (refer to the first bullet point in the next 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. We will also make the...

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