Generative Adversarial Network
A Generative Adversarial Network (GAN) is a class of machine learning frameworks that create new data instances that resemble your training data, even though the faces don’t belong to any real person. They achieve this level of realism by pairing a generator, which learns to produce the target output, with a discriminator, which learns to distinguish true data from the output of the generator.