Note for anyone signing up for this who has been in industry for a while: the prerequisites for this class really are prerequisites and it can be quite difficult to follow along if you're too busy trying to get your head around the basic math. You can check out the existing lectures on iTunes U to see what I mean.<p>Completing the Khan Academy playlists for Linear Algebra and Probability would be pretty useful if you want to be prepared in time for October.
Like a few other people here, I took this class recently. I did well, but I don't feel like I truly understand material until I teach it.<p>That being said, if anybody here has questions on the material, I'd love to help you out in some way. Unfortunately, there is no personal messaging feature on HN, so we might have to resort to emails (or maybe a subreddit?).<p>I realize there is an official class forum, so please tell me if you have any interest in some sort of 3rd party support system :-)
I took this class as CS 229 at Stanford, and will attest that it's pretty damn awesome (easily one of the best classes I've been able to take). The course really provides a thorough exploration of a lot of the main techniques in machine learning, and Prof. Ng also presents it in a very engaging and understandable way. This was one of the few classes where I enjoyed my 3-hour long midterm!<p>You can see the materials from this course's previous incarnation at <a href="http://www.stanford.edu/class/cs229/" rel="nofollow">http://www.stanford.edu/class/cs229/</a>
Signed up for this and AI.<p>Anyone know how many hours per week will be required? I am finishing up my 3 year distance learning MSc this month, so will have around 20 hours per week for these two courses. Hope that will be enough.
I've been meaning to follow along with the online collection of lectures from this course at some point, so I guess now's the time to actually dive in. I'm interested to see how a very rigorous course will be adapted to something that looks very similar to the Khan Academy model.