Machine Learning: Supervised Methods

Aalto University: Machine Learning: Supervised Methods, 5 ECTS. The course focuses on the following topics: Generalization error analysis and estimation Model selection Optimization and computational complexity Linear models Support vector machines and kernel methods Boosting Feature selection and sparsity Multilayer perceptrons Multi-class classification Ranking Multi-output learning Upon completion of the course, the student knows how to recognize and formalize supervised machine learning problems, how to implement basic optimization algorithms for supervised learning problems and how to evaluate the performance supervised machine learning models. The student has understanding of the statistical and computational limits of supervised machine learning, as well as the principles behind commonly used machine learning models.