Hyperparameters are parameters that are set before the training of an AI model. They control the behaviour and performance of the model, such as learning rate, batch size, and regularisation strength. Selecting appropriate Hyperparameters is crucial for optimising model performance and improving accuracy.
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…