Exercises for CSC's Practical Machine Learning course
See SETUP.md for instructions on how to set up Notebooks.
- Exercise 01: Introduction to Notebooks, Python, and numpy
- Exercise 02: Linear classifiers
- Exercise 03: Nearest neighbor classifiers
- Exercise 04: Linear and polynomial regression
- Exercise 05: Classification with SVMs
- Exercise 06: Regression with SVMs
- Exercise 07: Classification with decision trees
- Exercise 08: Regression with decision trees
- Exercise 09: Classification with neural networks
- Exercise 10: Regression with neural networks
- Exercise 11: Dimensionality reduction
- Exercise 12: Data visualization
- Exercise 13: Clustering
- Exercise 14: Anomaly detection
- Extra 01: Classification with naive Bayes
- Extra 02: Parameter grid search for SVM classification
- Extra 03: Ensemble of classifiers