Introduction to Machine Learning

This course is an elective aimed at 2nd (or 3rd) year BSc EE students. During the course students are exposed to the basics of machine learning (ML) suited for electrical engineering students. The topics include: Mathematical optimisation, regression and classification, linear unsupervised learning, neural networks and tree-based learners. We will use the Python programming language in this course.

The final grade of the course consists of the following components:- project report (0.5)- final exam (0.5)- assignments (p/f)Final grade calculation: (0.5 * project + 0.5 * written exam)* students should receive a minimum of 6 (out of 10) in each item to pass the course In case of an insufficient final result, repair options may exist in accordance with Article 17A Times and number of examinations, sub 1, of the Teaching and Examination Regulations 2024-2025.Disclaimer: information may change depending on unforeseen circumstances or measures (see: TER Art 2, sub 5).