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.
Forecasting involves predicting future outcomes or trends based on historical data and patterns. By analysing past data and applying statistical techniques, businesses can make…