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Deep Learning with TensorFlow and Keras – 3rd edition

You're reading from   Deep Learning with TensorFlow and Keras – 3rd edition Build and deploy supervised, unsupervised, deep, and reinforcement learning models

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Product type Paperback
Published in Oct 2022
Publisher Packt
ISBN-13 9781803232911
Length 698 pages
Edition 3rd Edition
Tools
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Authors (3):
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Sujit Pal Sujit Pal
Author Profile Icon Sujit Pal
Sujit Pal
Antonio Gulli Antonio Gulli
Author Profile Icon Antonio Gulli
Antonio Gulli
Dr. Amita Kapoor Dr. Amita Kapoor
Author Profile Icon Dr. Amita Kapoor
Dr. Amita Kapoor
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Toc

Table of Contents (23) Chapters Close

Preface 1. Neural Network Foundations with TF 2. Regression and Classification FREE CHAPTER 3. Convolutional Neural Networks 4. Word Embeddings 5. Recurrent Neural Networks 6. Transformers 7. Unsupervised Learning 8. Autoencoders 9. Generative Models 10. Self-Supervised Learning 11. Reinforcement Learning 12. Probabilistic TensorFlow 13. An Introduction to AutoML 14. The Math Behind Deep Learning 15. Tensor Processing Unit 16. Other Useful Deep Learning Libraries 17. Graph Neural Networks 18. Machine Learning Best Practices 19. TensorFlow 2 Ecosystem 20. Advanced Convolutional Neural Networks 21. Other Books You May Enjoy
22. Index

CycleGAN in TensorFlow

In this section, we will implement a CycleGAN in TensorFlow. The CycleGAN requires a special dataset, a paired dataset, from one domain of images to another domain. So, besides the necessary modules, we will use tensorflow_datasets as well. Also, we will make use of the library tensorflow_examples, we will directly use the generator and the discriminator from the pix2pix model defined in tensorflow_examples. The code here is adapted from the code here https://github.com/tensorflow/docs/blob/master/site/en/tutorials/generative/cyclegan.ipynb:

import tensorflow_datasets as tfds
from tensorflow_examples.models.pix2pix import pix2pix
import os
import time
import matplotlib.pyplot as plt
from IPython.display import clear_output
import tensorflow as tf

TensorFlow’s Dataset API contains a list of datasets. It has many paired datasets for CycleGANs, such as horse to zebra, apples to oranges, and so on. You can access the complete list here: https://www...

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