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?
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...
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/