New data mining course
Date: 25 Jul 2001 00:37:24 GMT
Message-ID: <9jl4c4$arq$14_at_usenet.Stanford.EDU>
This two-day course gives a detailed overview of statistical models for data mining, inference and prediction. With the rapid developments in internet technology, genomics and other high tech industries, we rely increasingly more on data analysis and statistical models to exploit the vast amounts of data at our fingertips.
This sequel to our popular Modern Regression and Classification course covers many new areas of unsupervised learning and data mining, and gives an in-depth treatment of some of the hottest tools in supervised learning.
The first course is not a pre-requisite for this new course.
Day one focusses on state-of-art methods for supervised learning including PRIM, boosting and support vector machines. Day two covers unsupervised learning including clustering, principal components, principal curves and self-organizing maps. Many applications will be discussed, including DNA expression arrays. These are one of the hottest new areas in biology!
###################################################Much of the material is based on the upcoming book:
Elements of Statistical Learning: data mining, inference and prediction
(with J. Friedman, Springer -Verlag, 2001).
A copy of this book will be given to all attendees.
###################################################
The first offering of this new course will take place Sep 6-7, 2001, in Cambridge, Mass.
Further details are available at
http://www-stat.stanford.edu/~hastie/mrc.html
Please Email me if you have specific questions
(tibs_at_stat.stanford.edu).
-- ********************************************** Rob Tibshirani, Dept of Health Research & Policy and Dept of Statistics HRP Redwood Bldg Stanford University Stanford, California 94305-5405 phone: HRP: 650-723-7264 (Voice mail), Statistics 650-723-1185 FAX 650-725-8977 tibs_at_stat.stanford.edu http://www-stat.stanford.edu/~tibsReceived on Wed Jul 25 2001 - 02:37:24 CEST