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.
Machine Learning is a powerful branch of Artificial Intelligence (AI) that focuses on enabling computer systems to learn and improve from experience without being…