How do the generator and discriminator components of a GAN interact during training?

  • The generator produces real data.
  • The discriminator generates fake data.
  • The generator tries to fool the discriminator.
  • The discriminator generates real data.
In a GAN (Generative Adversarial Network), the generator creates fake data to deceive the discriminator, which aims to distinguish between real and fake data. This adversarial process improves the quality of the generated data.
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