Part 3: Machine Learning


Tuesday (theory) Thursday (lab)
10-12 Nov. [Theory] Intro to ML; k-nearest neighbors and decision trees (slides) Javier's last session.
17-19 Nov. Javier's Exam (Nov. 17) [Lab] Environment setup, and intro to dataset loading/visualization. First classification tasks (files)
24-26 Nov. [Theory] Linear and Logistic Regression (slides) [Theory] Evaluation of classifiers (slides)
1-3 Nov. [Lab] Cross-validation, underfitting and overfitting, hyperparameter tuning with grid search (files) [Theory] Unsupervised learning (slides)
8-10 Dec. FESTA [Lab] Unsupervised learning (notebook)
15-17 Dec. Examen ML (Dec. 15) Projecte