GAN

Generative Adversarial Network (GAN) is a machine learning architecture that uses two neural networks a generator and a discriminator to compete with each other during training. The generator creates synthetic data such as images, audio, or other content, while the discriminator evaluates whether that data appears real. GANs are widely used in generative AI, image synthesis, data augmentation, and other deep learning applications where realistic artificial data is valuable.