Syllabus
- Foundations of machine learning;
- Review and assessment of the main algorithms;
- Ensemble methods;
- Models quality control;
- Shallow and deep learning;
- Processing workflows development;
- Projects on applications in geosciences (three different topics);
Annotation
Machine learning has become a significant data science tool to explore and analyze the geography data. The objectives of the course is to review basic principles of machine learning, critically assess the algorithms, practically design processing workflows, apply quality control procedures and interpret the results.
The analysis are applied on spatial and spatio-temporal geography data. Students will develop their own scripts to practically use the gained knowledge of machine learning within the geoscience applications.
There are no formal prerequisites, but a good knowledge of Python language is necessary.