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.
Deep Reinforcement Learning is a subset of Machine Learning that combines Deep Learning and Reinforcement Learning. It involves training AI models to make decisions…
