Generative models are the family of machine learning models that are used to describe how data is generated. To train a generative model we first accumulate a vast amount of data in any domain and later train a model to create or generate data like it.
In other words, these are the models that can learn to create data that is similar to data that we give them. One such approach is using Generative Adversarial Networks (GANs), which will be discussed as part of this chapter in detail.
The following topics will be covered in this chapter:
- Introduction to generative models
- GANs
