What is the difference between a parametric and non-parametric model?

A parametric model makes assumptions about the distribution of the data and estimates a fixed set of parameters that describe the model. Examples of parametric models include linear regression and logistic regression. Non-parametric models, on the other hand, do not make assumptions about the distribution of the data and instead estimate the underlying function directly from the data. Examples of non-parametric models include decision trees and support vector machines.