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| From | Scott Merryman <scott.merryman@gmail.com> |
| To | statalist@hsphsun2.harvard.edu |
| Subject | st: Statistical Learning online course |
| Date | Thu, 19 Dec 2013 15:38:50 -0600 |
Trevor Hastie and Robert Tibshirani are teaching online course (through Stanford's OpenEdX) on statistical learning using R. http://online.stanford.edu/course/statistical-learning-winter-2014 ABOUT THIS COURSE This is an introductory-level course in supervised learning, with a focus on regression and classification methods. The syllabus includes: linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (ridge and lasso); nonlinear models, splines and generalized additive models; tree-based methods, random forests and boosting; support-vector machines. Some unsupervised learning methods are discussed: principal components and clustering (k-means and hierarchical). * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/