Verde is a Python library for processing spatial data (bathymetry, geophysics surveys, etc) and interpolating it on regular grids (i.e., gridding). Most gridding methods in Verde use a Green’s functions approach. A linear model is estimated based on the input data and then used to predict data on a regular grid (or in a scatter, a profile, as derivatives). The models are Green’s functions from (mostly) elastic deformation theory. This approach is very similar to machine learning so we implement gridder classes that are similar to scikit-learn regression classes. The API is not 100% compatible but it should look familiar to those with some scikit-learn experience.