Standalone mode to process big data and collect some useful open-source tools

1. libfm

Project home: http://www.libfm.org/

2. svdfeature

Project home: http://apex.sjtu.edu.cn/apex_wiki/svdfeature

3. libsvm and liblinear

Libsvm project home page: http://www.csie.ntu.edu.tw /~ Cjlin/libsvm/

Liblinear project home page: http://www.csie.ntu.edu.tw /~ Cjlin/liblinear/

Required for first use: Practical Guide

Libsvm development experience by Lin zhiren: http://www.csie.ntu.edu.tw /~ Cjlin/talks/kdd.pdf

4. RT-rank

Project homepage: http://research.engineering.wustl.edu /~ Amohan/

RT-rank provides the following methods: Random forests and gradient boosted demo-trees, which are common in recommendation systems.

3. mahout

Project home: http://mahout.apache.org/

4. mymedialist

Project home: http://www.ismll.uni-hildesheim.de/mymedialite/

4. graphlab and graphchi

Graphlab project home: http://graphlab.org/

Graphchi project home: http://graphlab.org/graphchi/

Graphchi: https://code.google.com/p/graphchi/downloads/detail? Name1_graphchi_src_v0.1.2_toolkits.tar.gz

Graphchi Introduction: http://www.technologyreview.com/news/428497/your-laptop-can-now-analyze-big-data? Nlid = nldly & NLD = 2012-07-17

CF for graphchi: http://bickson.blogspot.com/2012/08/collaborative-filtering-with-graphchi.html