Foundations of Machine Learning
published: March 11, 2008, recorded: March 2008, views: 1705
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.
Machine learning is usually taught as a bunch of methods that can solve a bunch of problems (see above).
The second part of the tutorial takes a step back and asks about the foundations of machine learning, in particular the (philosophical) problem of inductive inference, (Bayesian) statistics, and artificial intelligence.
It concentrates on principled, unified, and exact methods.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !