Machine Learning

The course is part of the programme MAISTR (hh.se/maistr) where participants can take the entire programme or individual courses. The course is for professionals and is held online in English. The courses qualify for credits and are free of charge for participants who are citizens of any EU or EEA country, or Switzerland, or are permanent residents in Sweden. More information can be found at antagning.se. <br> The course covers the following topics: - Introduction to machine learning, including basics and prerequisites. - Basic aspects of supervised machine learning, including basic regression and classification algorithms. - Overfitting and generalization, the bias/variance trade-off, and methods for avoiding overfitting, including regularization. Explanation of how these problems are addressed in various methods, including Support Vector Machines (SVMs), and ensemble methods. - Introduction to Neural Networks for supervised learning, as well as an overview of deep neural networks and unsupervised feature extraction with autoencoders. - Overview of unsupervised data clustering methods and their applications.