Today our EAGLE students applied data munging, pipes, plotting and statistics using colour distribution of sweets. They specifically used the dplyr, ggplot, kableExtra and others to compute derivatives, rearrange the data, plot it and run statistics on colour distribution differences between different sweet packages. After this initial task of the course “spatial prediction and modelling” actual spatial prediction of in-situ point data combined with remote sensing data will be performed. This course will cover a wide range of approaches and packages to run spatial models and predict them spatially and temporally.
EAGLE MSc Defense: Machine Learning Inference of Building Basement Presence Using Street-Level Imagery and Multi-Source Geospatial Attributes: A Case Study of Mannheim, Germany
On July 01, 2026, Gökçe Yağmur Özcan will present her Master Thesis on " Machine Learning Inference of Building Basement Presence Using Street-Level Imagery and Multi-Source Geospatial Attributes: A Case Study of Mannheim, Germany " at 11:00 at the EORC...









