There are several demos exemplifying the use of pyGPs for various Gaussian process () tasks.
We recommend to first go through *Basic GP Regression* which introduces the regression model.
Basic regression is the most intuitive and simplest learning task feasable with .
The other demos will then provide a general insight into more advanced functionalities of the package.
You will also find the implementation of the demos in the source folder under pyGPs/Demo.

The Demos give some theoretical explanations. Further, it is useful to have a look at our documentation on Kernels & Means and Optimizers.

Regression

Classification

Some examples for real-world data