What are GANs?

Before we discuss GANs, you should know how generative models work. But before that, it would be advisable to understand how generative models are different from discriminative models.

Differences between Discriminative and Generative models

DL models can be broadly divided into discriminative models and generative models. Simply put, discriminative models focus on generating predictions of labels from the features mainly used for supervised learning (SL), and generative models focus on explaining how the data is generated and are used for unsupervised learning (UL). Let’s go into this a little deeper to understand the differences.

Discriminative models try to find the relationships between , such as features, and , such as targets. For example, if you are trying to predict the cancer type from genomic variations (single nucleotide polymorphisms, or SNPs), the here indicates the features of those data instances such as the number of variations, type...