Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Generative Adversarial Networks Projects
  • Toc
  • feedback
Generative Adversarial Networks Projects

Generative Adversarial Networks Projects

By : Ahirwar
2.3 (3)
close
Generative Adversarial Networks Projects

Generative Adversarial Networks Projects

2.3 (3)
By: Ahirwar

Overview of this book

Generative Adversarial Networks (GANs) have the potential to build next-generation models, as they can mimic any distribution of data. Major research and development work is being undertaken in this field since it is one of the rapidly growing areas of machine learning. This book will test unsupervised techniques for training neural networks as you build seven end-to-end projects in the GAN domain. Generative Adversarial Network Projects begins by covering the concepts, tools, and libraries that you will use to build efficient projects. You will also use a variety of datasets for the different projects covered in the book. The level of complexity of the operations required increases with every chapter, helping you get to grips with using GANs. You will cover popular approaches such as 3D-GAN, DCGAN, StackGAN, and CycleGAN, and you’ll gain an understanding of the architecture and functioning of generative models through their practical implementation. By the end of this book, you will be ready to build, train, and optimize your own end-to-end GAN models at work or in your own projects.
Table of Contents (11 chapters)
close

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.

bookmark search playlist download font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete