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Deep Learning By Example

You're reading from  Deep Learning By Example

Product type Book
Published in Feb 2018
Publisher Packt
ISBN-13 9781788399906
Pages 450 pages
Edition 1st Edition
Languages
Toc

Table of Contents (18) Chapters close

Preface 1. Data Science - A Birds' Eye View 2. Data Modeling in Action - The Titanic Example 3. Feature Engineering and Model Complexity – The Titanic Example Revisited 4. Get Up and Running with TensorFlow 5. TensorFlow in Action - Some Basic Examples 6. Deep Feed-forward Neural Networks - Implementing Digit Classification 7. Introduction to Convolutional Neural Networks 8. Object Detection – CIFAR-10 Example 9. Object Detection – Transfer Learning with CNNs 10. Recurrent-Type Neural Networks - Language Modeling 11. Representation Learning - Implementing Word Embeddings 12. Neural Sentiment Analysis 13. Autoencoders – Feature Extraction and Denoising 14. Generative Adversarial Networks 15. Face Generation and Handling Missing Labels 16. Implementing Fish Recognition 17. Other Books You May Enjoy

An intuitive introduction

In this section, we are going to introduce GANs in a very intuitive way. To get an idea of how GANs work, we will adopt a fake scenario of getting a ticket for a party.

The story starts with a very interesting party or event being held somewhere, and you are very interested in attending it. You hear about this event very late and all the tickets are sold out, but you will do anything to get into the party. So you come up with an idea! You will try to fake a ticket that needs to be exactly the same as the original one, or very, very similar to it. But because life is not easy, there's another challenge: you don't know what the original ticket looks like. So from your experience of going to such parties, you start to imagine what the ticket might look like and start to design the ticket based on your imagination.

You will try to design the ticket...

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