Data Mining Resources
- Advice for Applying Machine Learning (by Dr Andrew Ng)
http://cs229.stanford.edu/materials/ML-advice.pdf - Linear Algebra Review and Reference
http://cs229.stanford.edu/section/cs229-linalg.pdf - Vowpal wabbit (project to design a fast, scalable learning method by John Langford)
video: http://videolectures.net/nipsworkshops2010_langford_vow/
- Large Scale Machine Learning Class from NYU (by Yann LeCun and John Langford)
http://cilvr.cs.nyu.edu/doku.php?id=courses:bigdata:start - PEGASUS: A Peta-scale graph mining system
http://www.cs.cmu.edu/~pegasus/what%20is%20pegasus.htm - Parallel SVM
http://code.google.com/p/psvm/ - Twister: Iterative MapReduce
http://www.iterativemapreduce.org/ - RHadoop (R + Hadoop)
http://cos.name/2013/03/rhadoop1-hadoop/
http://cos.name/2013/03/rhadoop2-rhadoop/
Video Lectures
- Machine learning from Stanford (by Dr. Andrew Ng)
http://cs229.stanford.edu/materials.html - Introduction to Statistics from Berkeley
http://t.cn/zYxWfhr - Machine Learning Course from Caltech
http://work.caltech.edu/telecourse.html - Machine Learning Video Lectures from CMU (by Dr. Alex Smola and Barnabas Poczos):
http://alex.smola.org/teaching/cmu2013-10-701/intro.html