AI engineering glossary · Classical ML algorithms
What is GP (gaussian process)?
Gaussian process (also called GP): A flexible model that defines a probability distribution over functions using a kernel to describe how outputs relate. It gives predictions along with uncertainty and works well on small datasets, but scales poorly with rows.
Gaussian process: an example
Fitting 30 expensive lab experiments and getting both a predicted yield and a confidence band at untested settings.
Related terms
More Classical ML algorithms terms
Where you learn it
Gaussian process is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.