6. Generative adversarial networks (GANs) _ "2. Introduction to AI algorithms"

Generative adversarial networks (GANs) use two neural networks trained adversarially to generate realistic data.

1. Real data, providing data features to the generator.

   
   

2. Generator

   - Responsible for "generating" fake data, trying to mimic the distribution of real data.

   - Try to generate fake data that can fool the discriminator

   - The goal is to minimize the difference between generated data and real data

3. Generator generates data

4. Discriminator

   - Responsible for “distinguishing” real data from generated fake data.

   - Try to accurately identify real data from fake data.

   - The goal is to maximize its recognition accuracy