Homework, practices and projects for the Machine Learning course.
- Act_1: Describing a DataSet.
- Act_2: Data imputation and Normalization.
- Act_3: K-Means and Affinity Propagation.
- Act_4: Decision Tree.
- Ex_1: K Nearest Neighbours (KNN).
- Ex_F: Pricing Analytics.
- Practicas: Includes all the extra activities.
- DB: Contains all datasets used in this course.
- utils: Contains libraries created for the activities.