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Geo Data Science
| Term | SPW | Type | Lecturer | Person in charge |
|---|---|---|---|---|
| 2nd. (SS) | 4 | Lecture Exercises | Prof. Dr.-Ing. Martin Kada | Prof. Dr.-Ing. Martin Kada |
Course content
- Exploratory thematic and spatial data analysis (with Python)
- Statistical analytics
- Correlation, data manipulation and cleaning
- Feature extraction from geographical data
- Supervised vs. unsupervised learning
- Linear and polynomial regression
- Regularized linear models
- Logistic and multinomial logistic regression
- Cost functions
- Model training and fine-tuning
- Gradient descent, learning curves, performance measures
- Support vector machines
- Decision trees, random forests, ensemble learning, dimensionality reduction
- Segmentation and clustering (k-means, hierarchical clustering, DBSCAN)
- Privacy and ethics in data science
- Python numerical, scientific, and machine learning libraries