GAN
Definition | : | Generative Adversarial Network |
Category | : | Computing » Programming & Development |
Country/Region | : | Worldwide |
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Type | : |
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What does GAN mean?
Generative Adversarial Network (GAN) is a Machine Learning (ML) model used in unsupervised learning. GAN works by two neural networks consist of a generator and a discriminator competing against each other in a zero-sum game framework to become more accurate in their predictions.
In GAN, the generator will constantly try to outsmart the discriminator by generating better and better fakes, while the discriminator tries to become a better detective and correctly classify the real and fake data from the output of the generator.
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Frequently Asked Questions (FAQ)
What is the full form of GAN in Machine Learning ?
The full form of GAN is Generative Adversarial Network
What is the full form of GAN in Computing?
Generative Adversarial Network
What are the full forms of GAN in Worldwide?
Gallium Nitride | Generative Adversarial Network | Generic Access Network | Giant Axonal Neuropathy | Global Arab Network