EDIT: I’ve started a home for machine learning folks powered by Eggsprout at http://machine-learning.eggsprout.com. Please join me and bring others like us together. Don’t be alarmed if the site is a little empty now, all communities have to start somewhere .
If you’re that kind of person and you somehow came across this blog, here’s what I’ve found useful so far:
Stanford CS229 Machine Learning Course on Youtube: Probably the most useful and relevant resource for a beginner. I somewhat enjoy Andrew Ng’s teaching style. I bet he’d be a great mentor to have for research. The way the course is organized is very different from how professor Pedro Domingos taught us though. Not far enough in the series to say whether I like it more or not.
CS229 Lecture Notes: Lecture notes that accompany the Youtube videos.
UW Part-time Masters Lectures: Taught by professor Pedro Domingos, awesome teacher and incredibly genius.
VideoLectures.net: These look like they’d be more advanced but interesting nonetheless. So much to watch… so little time.
ResearchChannel.org: I love this resource for just about any topic. I’ve spent hours on this studying neurobiology back when I first entered college. Hopefully the machine learning topics here are just as interesting.
Machine Learning Data Repository: Nice repository of data for when you’re ready to practice using an algorithm. One of my homework assignments from college was from here.
Ruby A.I Plugins: A few ruby machine learning libraries. I’m a rubyist and it’d be nice to see more of these. Maybe I’ll contribute to these some day .
Tegu: A machine learning system in Ruby developed by David Richards. He looks like an interesting character and I’m keeping an eye on him and his projects. I like his dedication to ruby and machine learning.
Aside: Why do Google searches on “Machine Learning” always turn up results about sewing machines?