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GAN

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TL;DR. Abbreviation for Generative Adversarial Network, a class of machine learning frameworks.

Technical Definition

Abbreviation for Generative Adversarial Network, a class of machine learning frameworks.

How it works

GAN stands for Generative Adversarial Network. It refers to a type of generative model composed of two neural networks, a generator and a discriminator, that compete against each other. The generator creates new data instances, while the discriminator tries to distinguish between real data and the generated data, leading to increasingly realistic outputs.

Related Concepts

  • Deep Learning — A subset of machine learning using neural networks with many layers to learn hierarchical representations from large datasets.
  • Generative Adversarial Network (GAN) — Two neural networks — a generator and discriminator — compete against each other to produce increasingly realistic synthetic data.
  • Unsupervised Learning — Learning patterns from data that has no labels — only the inputs.
  • Generative AI — An AI field focused on creating models that can generate novel and complex content, such as text, images, audio, and video, that is coherent and original.

Further Reading

  • Google ML Glossary