Applied Machine Learning (MSc)
Informatics (INFR11211), Semester 1, 2025
Week 8 Announcement
Below are your tasks for this week.
Q&A Session
- Attend this week’s class session: Tue 04th at 4:10pm at 40 George Sq., Lecture Theatre A
Lectures
- Watch the videos for the two new lecture topics for week 6 - Recommender Systems and Neural Networks.
- The links to the videos and slides are on the Schedule page. We will discuss these in the Q&A session in week 9.
- Ask questions on Piazza for any parts you are not clear about.
Labs
- After you have finished this week’s tutorials and lectures, start Lab 4 which will take place next week.
- The solution to Lab 3 is now online.
Tutorials
- Attend Tutorial 3 this week in Appleton Tower 5.04.
- The solutions for Tutorial 3 will be online at the end of this week.
Coursework
- Keep up progress on your coursework.
- Note in particular the course policy on extensions (not allowed)! See the course information page for more details.
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.