GAN

What Does GAN Mean?

GAN means "Generative Adversarial Network."

TL;DR

Generative Adversarial Networks (GANs) consist of two parts: a Generator that creates fake data, and a Discriminator that tries to tell if the data is real or fake. They work together to create very realistic-looking data.

In Detail

GANs are a class of artificial intelligence (AI) algorithms used in unsupervised machine learning (ML). They have various applications, including image generation, style transfer, and data augmentation.

GANs consist of two neural networks, the Generator and the Discriminator, which are trained simultaneously. The Generator creates data that is similar to some real data, while the Discriminator evaluates it, trying to distinguish between real and fake data. The networks are in essence "adversaries," with the Generator trying to create convincing fakes, and the Discriminator trying to get better at spotting them. This adversarial process leads to the Generator creating highly realistic data.

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Image for GAN

When I write GAN, I mean this:

"Generative Adversarial Network"

Summary of Key Points

"Generative Adversarial Network" is the most common definition for GAN on Snapchat, WhatsApp, Facebook, Twitter, and Instagram. Here is some more information about GAN.

GAN
Definition:	Generative Adversarial Network
Type:	Acronym
Guessability:	4: Difficult to guess
Typical Users:	Specialists

Example of GAN Used in a Text

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