You're reading from Generative Adversarial Networks Projects

Product typeBook

Published inJan 2019

Reading LevelIntermediate

PublisherPackt

ISBN-139781789136678

Edition1st Edition

Languages

Python

Tools

TensorFlow Keras

Concepts

Deep Learning

Author (1)

Kailash Ahirwar

Summary

In this chapter, we learned about what a GAN is and which components constitute a standard GAN architecture. We also explored the various kinds of GANs that are available. After establishing the basic concepts of GANs, we moved on to looking at the underlying concepts that go into the construction and functioning of GANs. We learned about the advantages and disadvantages of GANs, as well as the solutions that help overcome those disadvantages. Finally, we learned about the various practical applications of GANs.

Using the fundamental knowledge of GANs in this chapter, we will now move on to the next chapter, where we will learn to generate various shapes using GANs.

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Published in: Jan 2019Publisher: PacktISBN-13: 9781789136678

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Author (1)

Kailash Ahirwar

Kailash Ahirwar is a machine learning and deep learning enthusiast. He has worked in many areas of Artificial Intelligence (AI), ranging from natural language processing and computer vision to generative modeling using GANs. He is a co-founder and CTO of Mate Labs. He uses GANs to build different models, such as turning paintings into photos and controlling deep image synthesis with texture patches. He is super optimistic about AGI and believes that AI is going to be the workhorse of human evolution.
Read more about Kailash Ahirwar

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