Machine Learning for Geographic Data

Optional statistical learning chapters for readers ready to go further.

Topic Library

Machine Learning for Geographic Data

This branch introduces statistical learning methods for geographic data. It is best treated as later-stage material after the modelling and GIS foundations already feel comfortable.

Open the Library Methods and Tools
2 chapters Extension material Machine learning
Library Route

This Mini-Library Moves From Prediction To Structure Discovery

The machine-learning branch is small enough that the route can be shown directly. First learn prediction for continuous geographic variables, then use dimensionality reduction to inspect hidden structure in high-dimensional data.

1

Regression

Model a continuous target from spatial or environmental predictors.

2

Dimensionality reduction

Compress high-dimensional structure into a form humans can inspect visually.

The machine-learning route starts with supervised prediction, then shifts to exploratory structure-finding in richer feature spaces.

Chapter Map