learning from data 1

This is a course for basic data analysis, statistical model building and machine learning. The course aims to provide a set of tools that I hope you will find very useful, coupled with a principled approach to formulating solutions to problems in machine learning.

Please look here for details of the course aims, and a brief overview of the material to be covered.

Lectures are in Appleton Tower, Theatre 2 :
Monday 5-6 and Wednesday 1-2
Lectures commence 7th October


I'm David Barber, a member of the Institute for Adaptive and Neural Computation

Announcements

You should check here regularly for important annoucements.

Introduction to LFD1

Even if you decide not to take the exam in LFD1 I recommend that you keep going to the lectures, since I think that you will find it interesting and hopefully useful.

Timm Mills is the module representative -- thanks Tim! Tim will filter your viewpoints on the course to me.

There's a bug in the `linear dimension reduction' notes on page 3. The equation in the third point in the PCA algorithm should be y^{\mu}=E^T(x^{\mu} - m) where m is the mean of the data.

PLEASE MAKE USE OF THE MATHS SURGERIES -- THEY WILL RUN FOR ONLY THE FIRST SIX WEEKS OF TERM1 details

tutorials

Each week (commencing Monday 14 October) there are tutorials. Each person attends 1 hour a week.

Attendence is compulsory for those that wish to get credit for this course.
details

mathematics

Some of you may struggle with the mathematics in this course. Please click on the link below for help. details