Ask HN: Good resources for learning about ML/AI?

[aviraldg]

Hey HN.

I've recently started learning about Machine Learning from Stanford's CS229 lecture videos and I was wondering if people with more experience could point me to (preferably free) supplementary resources for the same?

[glamp]

Berkley Course: http://alex.smola.org/teaching/berkeley2012/statistics.html

Scikit-Learn Docs: http://scikit-learn.org/dev/

Google Research: http://research.google.com/pubs/papers.html

Caltech Course: http://work.caltech.edu/telecourse.html

Basics in R: http://www.statmethods.net/advstats/glm.html

R packages for data science: http://blog.yhathq.com/posts/10-R-packages-I-wish-I-knew-abo...

[r41nbowcrash]

Weka: http://www.cs.waikato.ac.nz/ml/weka/

Lets you test dozens of different algorithms on a given dataset, to see what works and what not, in like one evening.

Also success stories from Kaggle competition: http://blog.kaggle.com/category/dojo/

[m_ke]

http://videolectures.net/Top/Computer_Science/ has a ton of lectures and conference talks from the top researchers in ML and AI

[jclos]

Jenn Vaughan's class notes at http://www.cs.ucla.edu/~jenn/courses/F11.html are really good in my opinion.