Course description
Welcome to Introduction to Machine Learning!
This webpage will be the main portal for the course. Most things you need will be available here. The exceptions are:
- PDF of slides and optional tutorial materials: available on Scientia
- Announcements and questions/answers/discussions: on Ed
Guided Study Materials
Please go through the study materials before the live interactive session.
Lectures
The live interactive Q&A session will run on Thursdays 14:00-15:00 from Week 2 onwards. These will be held at Huxley 308.
Lab
The lab sessions will be held on Tuesdays 14:00-16:00 from Weeks 2 to 8 (inclusive). These will be held at Huxley 202/206.
The lab sessions are for you to work on your coursework and the optional lab exercises. Tutorial helpers will be available to support you and help you with any queries.
Coursework
There will be two coursework assignments. Please see the schedule below for the deadlines for these.
Course plan
| Week | Date | Lecture | Lab | Coursework |
|---|---|---|---|---|
| 1 | 9/1/2023 | - | - | |
| 2 | 16/1/2023 | Machine Learning: The Big Picture | Lab | |
| 3 | 23/1/2023 | K Nearest Neighbours and Decision Trees | Lab | Coursework 1 released (Mon 23 Jan) |
| 4 | 30/1/2023 | Evaluation of Machine Learning Systems | Lab | |
| 5 | 6/2/2023 | Neural Networks (Part 1) | Lab | Coursework 1 due (Fri 10 Feb 19:00 GMT) |
| 6 | 13/2/2023 | Neural Networks (Part 2) | Lab | Coursework 2 released (Mon 13 Feb) |
| 7 | 20/2/2023 | Unsupervised Learning: Clustering and Density Estimation | Lab | |
| 8 | 27/2/2023 | Evolutionary Algorithms | Lab | Coursework 2 due (Fri 3 Mar 19:00 GMT) |
| 9 | 6/3/2023 | Revision | - | - |
Team
Instructors
Course assistants
Titus Buckworth
Course Support Leader
Mary Kenneth
Teaching Scholar
Tal Elbaz
Tutorial Assistant
Yifeng Mao
Tutorial Assistant