Neil Lawrence's opening course

Neil Lawrence is Professor at the University of Sheffield. He has worked on unsupervised learning for a long time, and has developed algorithms applicable to dimensionality reduction such as the Gaussian Process Latent Variable model (GP-LVM), see the JMLR paper here.

He has a superb inaugural lecture in which he talks about Machine Learning. The link to the starting page to see that video is here. It opens some embedded and annoying player but it is worth dealing with it.

Neil Lawrence's Inaugural Lecture

Title: Life, The Universe and Machine Learning

Time: 17:15 Thursday 6th September 2012

Venue: St George's Church Lecture Theatre, University of Sheffield

Abstract
What is Machine Learning? Why is it useful for us? Machine learning algorithms are the engines that are driving forward an intelligent internet. They are allowing us to uncover the causes of cancer and helping us understand the way the universe is put together. They are suggesting who your friends are on facebook, enabling driverless cars and causing flagging potentially fraudulent transactions on your credit card. To put it simply, machine learning is about understanding data.
In this lecture I will try and give a sense of the challenges we face in machine learning, with a particular focus on those that have inspired my research. We will look at applications of data modelling from the early 19th century to the present, and see how they relate to modern machine learning. There will be a particular focus on dealing with uncertainty: something humans are good at, but an area where computers have typically struggled. We will emphasize the role of uncertainty in data modelling and hope to persuade the audience that correct handling of uncertainty may be one of the keys to intelligent systems.