Statistical learning and data mining2010VTMasters level course
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Course plan
No of lectures
14*2 hours
Recommended for
Ph.D. students who are interested in extracting information form large or complex datasets
The course was last given
autumn 2008
Goals
The course lays the foundation for professional work and research in which large amounts of data are explored, modified, modelled and assessed to uncover previously unknown patterns and trends.
Prerequisites
Basic course in statistics/matehmatical statistics, linear algebra
Organization
Contents
Overview of supervised learning.
Literature
Hastie, Tiebshirani and Friedman. The elements of statistical learning ISBN: 0-387-95284-5
Lecturers
Anders Grimvall
Examiner
Anders Grimvall
Examination
Written lab reports
Credit
8 credits
Comments
Page responsible: Director of Graduate Studies