Machine Learning Models in Geodetic Data Science

Geodetic disciplines, such as navigation, engineering geodesy, photogrammetry and remote sensing employ machine learning algorithms for object tracking, clustering and segmentation of 3d point clouds, or predicting uncertainties of geodetic processes. This course will introduce you to the principles and algorithms that allow you to use training data to effectively make automated predictions based on data science techniques.

Module Contents

Introduction to machine Learning
Linear and nonlinear classification algorithms
Multiple linear and nonlinear regression
Regularization techniques in regression models (Ridge and LASSO regression)
Probabilistic based machine learning algorithms (Bayesian regression and Monte Carlo techniques)
Tree-based machine learning algorithms (random forest and XG Boost)
Neural networks