Meaning of Generative Adversarial Network (GAN)

Simple definition

A Generative Adversarial Network (GAN) consists of two neural networks – a generator and a discriminator – that work together to create realistic data from random noise.

How to use Generative Adversarial Network (GAN) in a professional context

GANs are used in generating realistic images, enhancing image resolution, creating deepfakes, and designing new products.

Concrete example of Generative Adversarial Network (GAN)

GANs are used to create synthetic images that look like real photographs, which can be useful in industries like gaming or fashion.