Supervised machine learning

Aalto University: Supervised machine learning, 5 ECTS. Course contents Generalisation error analysis and estimation Model selection Optimisation and computational complexity Linear models Support vector machines and kernel methods Boosting Feature selection and sparsity Multi-layer perceptrons Multi-class classification Preference learning Learning outcomes After the course, the student -knows how to recognise and formalise supervised machine learning problems, -knows how to implement basic optimisation algorithms for supervised learning problems, -knows how to evaluate the performance supervised machine learning models, -has understanding of the statistical and computational limits of supervised machine learning, as well as the principles behind commonly used machine learning models.