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.
An algorithm is a set of rules and instructions that guide AI systems in solving problems or making decisions. Algorithms process data, analyse patterns,…