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Machine Learning Using TensorFlow Cookbook

You're reading from   Machine Learning Using TensorFlow Cookbook Create powerful machine learning algorithms with TensorFlow

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Product type Paperback
Published in Feb 2021
Publisher Packt
ISBN-13 9781800208865
Length 416 pages
Edition 1st Edition
Languages
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Authors (3):
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Konrad Banachewicz Konrad Banachewicz
Author Profile Icon Konrad Banachewicz
Konrad Banachewicz
Luca Massaron Luca Massaron
Author Profile Icon Luca Massaron
Luca Massaron
Alexia Audevart Alexia Audevart
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Alexia Audevart
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Table of Contents (15) Chapters Close

Preface 1. Getting Started with TensorFlow 2.x 2. The TensorFlow Way FREE CHAPTER 3. Keras 4. Linear Regression 5. Boosted Trees 6. Neural Networks 7. Predicting with Tabular Data 8. Convolutional Neural Networks 9. Recurrent Neural Networks 10. Transformers 11. Reinforcement Learning with TensorFlow and TF-Agents 12. Taking TensorFlow to Production 13. Other Books You May Enjoy
14. Index

Convolutional Neural Networks

Convolutional Neural Networks (CNNs) are responsible for the major breakthroughs in image recognition made in the past few years. In this chapter, we will cover the following topics:

  • Implementing a simple CNN
  • Implementing an advanced CNN
  • Retraining existing CNN models
  • Applying StyleNet and the neural style project
  • Implementing DeepDream

As a reminder, the reader can find all of the code for this chapter available online here: https://github.com/PacktPublishing/Machine-Learning-Using-TensorFlow-Cookbook, as well as the Packt repository: https://github.com/PacktPublishing/Machine-Learning-Using-TensorFlow-Cookbook.

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