Generative Adversarial Networks are a type of Machine Learning model that consists of two neural networks: a generator and a discriminator. GANs are used to generate synthetic data that resembles real data by learning from training examples. They find applications in image generation, video synthesis, and data augmentation.
Bayesian networks are Probabilistic Graphical Models that represent and evaluate uncertainty and conditional dependencies between variables. Industries such as healthcare and finance use Bayesian…