Foundations of Machine Learning
author: Marcus Hutter,
Australian National University
published: March 11, 2008, recorded: March 2008, views: 14109
published: March 11, 2008, recorded: March 2008, views: 14109
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.
Description
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 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: