Research Computing Center

Machine Learning for Spatial Data

This workshop will provide a general overview of machine learning for spatial data , which will discuss its relevance and potential for spatial analysis. participants will gain an understanding of spatial feature engineering, geospatial data preprocessing, and regression and classification algorithms for spatial data. A few practical examples will be given as well as a vocabulary for further exploration. Hands-on exercises will be conducted in JupyterLab on the Midway3 cluster.

Objectives:

- Gain a general understanding of machine learning techniques for spatial data analysis

- Understand concepts related to geospatial data preprocessing and regression and classification models

- Learn to leverage High-Performance Computing resources for efficient spatial dataset processing

Level: Introductory

Duration: 2 hours

Prerequisites: Attendees should have a basic familiarity with spatial data/GIS. An RCC account is helpful but not required.

Register for Machine Learning for Spatial Data