EEX01 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.

Study Goals

After following this course you should be able to:

1. Explain the theoretical concepts behind machine learning algorithms and its challenges including data, feature extraction, model selection and evaluation.
2. Formulate practical real-world problems as mathematical equations (optimization problems) and solve them.
3. Design and implement various machine learning algorithms for real-world applications using python.

Teachers

Last modified: 2024-09-04