Variational Autoencoders are a type of generative model used in unsupervised learning. VAEs learn a low-dimensional representation of input data and can generate new data samples similar to the training data. They have applications in tasks such as image generation, anomaly detection, and data compression.
Deep Reinforcement Learning is a subset of Machine Learning that combines Deep Learning and Reinforcement Learning. It involves training AI models to make decisions…