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The Deep Learning Workshop

You're reading from   The Deep Learning Workshop Learn the skills you need to develop your own next-generation deep learning models with TensorFlow and Keras

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781839219856
Length 474 pages
Edition 1st Edition
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Authors (5):
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Nipun Sadvilkar Nipun Sadvilkar
Author Profile Icon Nipun Sadvilkar
Nipun Sadvilkar
Thomas Joseph Thomas Joseph
Author Profile Icon Thomas Joseph
Thomas Joseph
Anthony So Anthony So
Author Profile Icon Anthony So
Anthony So
Mohan Kumar Silaparasetty Mohan Kumar Silaparasetty
Author Profile Icon Mohan Kumar Silaparasetty
Mohan Kumar Silaparasetty
Mirza Rahim Baig Mirza Rahim Baig
Author Profile Icon Mirza Rahim Baig
Mirza Rahim Baig
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Toc

Table of Contents (9) Chapters Close

Preface
1. Building Blocks of Deep Learning 2. Neural Networks FREE CHAPTER 3. Image Classification with Convolutional Neural Networks (CNNs) 4. Deep Learning for Text – Embeddings 5. Deep Learning for Sequences 6. LSTMs, GRUs, and Advanced RNNs 7. Generative Adversarial Networks Appendix

Introduction

The power of creativity was always the exclusive domain of the human mind. This was one of the facts touted as one of the major differences between the human mind and the artificial intelligence domain. However, in the recent past, deep learning has been making baby steps in the path to being creative. Imagine you were at the Sistine Chapel in the Vatican and were looking up with bewilderment at the frescos immortalized by Michelangelo, wishing your deep learning models were able to recreate something like that. Well, maybe 10 years back, people would have scoffed at your thought. Not anymore, though – deep learning models have made great strides in regenerating immortal works. Applications like these are made possible by a class of networks called Generative Adversarial Networks (GANs).

Many applications have been made possible with GANs. Take a look at the following image:

Figure 7.1: Image translation using GANs

Note:

The preceding...

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