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.
Hyperparameters are parameters that are set before the training of an AI model. They control the behaviour and performance of the model, such as…