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Deep Learning with TensorFlow and Keras – 3rd edition - Third Edition

You're reading from  Deep Learning with TensorFlow and Keras – 3rd edition - Third Edition

Product type Book
Published in Oct 2022
Publisher Packt
ISBN-13 9781803232911
Pages 698 pages
Edition 3rd Edition
Languages
Authors (3):
Amita Kapoor Amita Kapoor
Profile icon Amita Kapoor
Antonio Gulli Antonio Gulli
Profile icon Antonio Gulli
Sujit Pal Sujit Pal
Profile icon Sujit Pal
View More author details

Table of Contents (23) Chapters

Preface 1. Neural Network Foundations with TF 2. Regression and Classification 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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