Geodetic Institute
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Lehrveranstaltungen
Machine Learning Models in Engineering Geodesy

Machine Learning Models in Engineering Geodesy

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

    Lecturer

    PD Dr.-Ing. Hamza Alkhatib
    Senior Research Staff
    Address
    Nienburger Straße 1-4
    30167 Hannover
    Building
    Room
    PD Dr.-Ing. Hamza Alkhatib
    Senior Research Staff
    Address
    Nienburger Straße 1-4
    30167 Hannover
    Building
    Room

    Exercise

    Marvin Scherff, M. Sc.
    Research Staff
    Address
    Nienburger Straße 1-4
    30167 Hannover
    Building
    Room
    Address
    Nienburger Straße 1-4
    30167 Hannover
    Building
    Room