Useful links and tools.
Data Mining and Machine Learning
Andrew’s Moore statistics and data mining tutorials
Gaussian Processes for Machine Learning (book)
Caltech Online Course: Learning from data
Web Services and standalone applications: DAME, Weka, Orange, VOStat
Books:
“Data Mining - Concepts and Techniques”, J. Han & M. Kamber, MK
“Neural Networks for Pattern Recognition”, C.M. Bishop, Oxford University Press
“Introduction to Information Retrieval”, Christopher D. Manning, Prabhakar Raghavan & Hinrich Schütze, 2008, Cambridge University Press
Programming Languages and DM Libraries
R: Official Manuals, Advanced R programming, R-Inferno, R-studio
Matlab: Official Documentation, SOM Toolbox, Bayesian Net Toolbox, Netlab
Software Architectures and Information Retrieval
Apache Tika (Content Detection and Analysis)
Joshua Decoder (Statistical Machine Translation)
Apache OODT (Big Data Processing)
Visualization Resources
Tools: d3js, plot.ly, Topcat, Processing
Modern Visualization Thinking:
https://vimeo.com/channels/544709
http://www.edwardtufte.com/tufte/
Historical Visualization Thinking:
http://en.wikipedia.org/wiki/%C3%89tienne-Jules_Marey
http://en.wikipedia.org/wiki/Charles_Joseph_Minard
