Working with a Generative Adversarial Network,Generative Adversarial Networks $($GANs$)$ are a powerful class of neural networks that are used for unsupervised learning. It was developed and introduced by Ian J$.$ Goodfellow in $2014.$ GANs are basically made up of two competing neural network models, which are able to analyze, capture, and copy the variations within a dataset.

Generative Adversarial Networks $($GANs$)$ can be broken down into three parts:

Generative: To learn a generative model, which describes how data is generated in terms of a probabilistic model.

Adversarial: The training of a model is done in an adversarial setting.

Networks: Use of deep neural networks as the artificial intelligence $($AI$)$ algorithms for training purposes