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Machine Learning and Pattern Recognition (MLPR), Autumn 2018

Machine learning is about developing algorithms that adapt their behaviour to data, to provide useful representations or make predictions. This course is for those wanting to research and develop machine learning methods in future. Those who want a more practical course, focussing more on using methods, should consider taking IAML instead. Informatics’ MSc handbook has more advice on choosing machine learning courses. Prospective students should work through the background material and self-test in the class notes.

ML-Base will run until Friday 30 November. Use it while you can!

Monday–Friday 5–6pm in AT-7.03 (the InfBase room). Drop in to meet other people studying MLPR, MLP, or IAML, and work on the courses together. If you can't resolve problems, a tutor will be circulating to advise.

Lecturer: Iain Murray
Lectures: Monday, Wednesday, Thursday 12:10–1pm.

Office Hours have now finished.
ML-Base: Drop in place to work with other ML students and get help. Mon–Fri, 5–6pm, InfBase (AT-7.03). Last one 30 Nov.
Lecture dates: 2018-09-17 to 2018-11-22.
Exam diet: December (more info).

If you want to ‘audit’ the class (take it not for credit), please watch the lecture recordings in the first week or two, while numbers attending the class are often inflated. Please also get your School to register you, following Informatics's auditing rules.

News

Please take the class survey

2018-11-19: Those enrolled on the class, please take the class survey. This one is viewed more broadly by the School and future prospective students.

2018-11-18: Exam preparation advice (alternative EASE link).

2018-11-15: Released tutorial 7 answers. (Tutorial 7 was the last tutorial.)

2018-10-23: Assignment 2 released.

2018-10-07: ML-Base, Monday–Friday 5–6pm in AT-7.03 (the InfBase room). Drop in to meet other people studying MLPR, MLP, or IAML, and work on the courses together. If you can't resolve problems, a tutor will be circulating to advise.

Archive of all news.

Course materials

There are links to each of these sections at the top of every page.

MLPR’s DRPS catalogue page.

MLPR’s Learn page.


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