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Machine Learning for spatial data

Duration Time 3 days
Level master

Machine Learning Algorithms are increasingly interesting for analyzing spatial data, especially to derive spatial predictions / for spatial interpolation and to detect spatial patterns. Spatial auto-correlation, especially if still existent in the cross-validation residuals, indicates that the predictions are maybe biased, and this is suboptimal, hence Machine Learning algorithms need to be adjusted to spatial data problems.

Course Features
Video lessons
10 case studies
Spatial prediction