What is Gaussian processes?

Gaussian Processes (GPs) are a powerful non-parametric Bayesian approach to machine learning. They are used for regression and classification tasks by defining a probability distribution over possible functions that fit the observed data. GPs provide not only predictions but also a measure of uncertainty associated with these predictions, making them particularly useful in situations where quantifying uncertainty is important. They are commonly used in applications such as time series forecasting, spatial statistics, and optimization.