Introduction to Machine Learning

author: Iain Murray, School of Informatics, University of Edinburgh
published: Aug. 5, 2010,   recorded: July 2010,   views: 12350
Categories

Slides

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Delicious Bibliography

 Watch videos:   (click on thumbnail to launch)

Watch Part 1
Part 1 49:14
!NOW PLAYING
Watch Part 2
Part 2 51:57
!NOW PLAYING
Watch Part 3
Part 3 1:27:21
!NOW PLAYING

Description

How can we represent data on a computer and use it to learn to perform useful tasks? This lecture reviews some simple classification and regression rules, discusses under- and over-fitting and emphasises the utility of defining objective functions for learning. There is also a short overview of Bayesian learning, and some practical tips for pre-processing and visualizing data. The lecture ends with a brief mention of unsupervised learning and related topics.

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: