Applied Machine Learning (MSc)
Informatics (INFR11211), Semester 1, 2025
Week 2 Announcement
Below are your tasks for this week.
Lectures
- Make sure you have watched the videos from week 1 so that you do not fall behind
- Watch the videos for the new lecture topics for week 2 - Naive Bayes Classification and Logistic Regression. The links to the videos and slides are on the Schedule page. We will discuss these in the Q&A session in week 3
- Ask questions on Piazza for any parts you are not clear about
Labs
- Check your personal timetable to see which lab group/time you have been assigned to
- Complete the introduction Lab 0. If you are having issues with this lab, please let us know on Piazza or during the class session in week 2
- Start working on Lab 1 in advance of your first scheduled lab session in week 3
In this course we will be introducing a number of machine learning methods and concepts, helping to understand how they work, and how to apply them.
Those wanting to conduct research in, and develop, machine learning methods should consider taking PMR (INFR11134) instead. For general information on different machine learning courses at Informatics, see here.
On successful completion of this course, you should be able to:
- Explain the scope, goals and limits of ML, and the main sub-areas of the field.
- Describe the various techniques covered and where they fit within the structure of the discipline.
- Apply the taught techniques to data, to solve ML problems, using appropriate software.
- Analyse ML techniques in terms of their limitations and applicability to different problems, as well as potential ethical concerns.
- Compare and evaluate the performance of ML techniques using systematic approaches to conducting experiments and assessing scientific hypotheses.