Introduction to Geospatial Machine Learning with SRAI

Tutorial offers a thorough introduction to the geospatial domain with Python libraries. Participants will learn how to use, analyse and visualize open-source geospatial data. Additionally, participants will learn to pre-train embedding models and train predictive models for downstream tasks.

Most of the tutorial will be showing capabilities of the library srai (Spatial Representation for Artificial Intelligence), as well as GeoPandas, Shapely, osmnx and scikit-learn.

Beginner knowledge of Python is expected from the participants. Tutorial materials is provided in the form of Jupyter notebooks.

At the end of each notebook there is a task for you to do. In the answers directory you'll find proposed solutions that you can copy and paste into the notebook.

Initialize Python virtual environment (optional but recommended):

python -m venv venv
source venv/bin/activate

And then install the dependencies:

pip install -r requirements.txt