Tools and techniques for data mining
This tutorial will provide a basic introduction to data mining and
statistical learning techniques.
Topics include: algorithms for data mining (e.g., clustering,
dimensionality reduction,
recommender systems, association rule mining), basic statistical modeling
(e.g., logistic and non-linear regression),
supervised learning (parametric/non-parametric algorithms, support vector
machines). The tutorial will also present some case studies applications together with
their implementation with the
R statistical programming language (www.r-project.org/).
References
Mining of Massive Datasets (http://i.stanford.edu/~ullman/mmds.html)