Introduction to Machine Learning
published: Aug. 5, 2010, recorded: July 2010, views: 91742
Report a problem or upload filesIf 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.
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 pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !