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About the course
1. Introduction
2. Modeling
3. Reading and plotting
4. Preprocessing and feature extraction
5. Dimensionality reduction by Subspace projections
6. Unsupervised learning
7. Training process
12. Nearest Neighbours methods
13. Support Vector Machine (SVM)
14. Decision trees and forests
15. Regression and regularisation
16. Artificial Neural Networks (ANN)
17. Model learning strategies
Index