Advanced Process Monitoring And Control – Politecnico di Torino

• Lecture slides and curated reading lists will be made available through the course platform. Curated code repositories with Jupyter notebooks, datasets, and laboratory templates will be provided for reproducible exercises.

Argomenti del programma: Data-driven modelling: datasets, preprocessing, feature engineering, training/validation/testing, bias-variance tradeoff, cross-validation. Classical machine learning methods: linear and nonlinear regression, regularization (Ridge, Lasso), logistic regression, decision trees, random forests, ensemble methods, support vector machines.