Intermediate · Generative AI

Generative Adversarial Networks (GANs)

Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.

TL;DR. A class of deep learning frameworks composed of two neural networks, a generator and a discriminator, competing against each other.

Technical Definition

A class of deep learning frameworks composed of two neural networks, a generator and a discriminator, competing against each other.

How it works

GANs learn to generate new data instances that resemble the training data, such as images, audio, or text. The generator creates fake data while the discriminator tries to distinguish real from fake. This adversarial process drives both networks to improve, producing highly realistic synthetic content.

Related Concepts

• Deep Learning — A subset of machine learning using neural networks with many layers to learn hierarchical representations from large datasets.
• Unsupervised Learning — Learning patterns from data that has no labels — only the inputs.