Free Stanford online course on Statistical Learning (with R) starting on 19 Jan 2015

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).

The lectures cover all the material in An Introduction to Statistical Learning, with Applications in R by James, Witten, Hastie and Tibshirani (Springer, 2013). As of January 5, 2014, the pdf for this book will be available for free, with the consent of the publisher, on the book website.

Classes Start: Jan 19, 2015
Classes End: Apr 03, 2015
Course Staff: Prof. Trevor Hastie, Prof. Rob Tibshirani
Price: Free
URL: https://class.stanford.edu/courses/HumanitiesandScience/StatLearning/Winter2015/about

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About Yanchang Zhao

I am a data scientist, using R for data mining applications. My work on R and data mining: RDataMining.com; Twitter; Group on Linkedin; and Group on Google.
This entry was posted in Data Mining, R and tagged , . Bookmark the permalink.

4 Responses to Free Stanford online course on Statistical Learning (with R) starting on 19 Jan 2015

  1. Pingback: Free Stanford online course on Statistical Learning (with R) starting on 19 Jan 2015 | Mubashir Qasim

  2. Pingback: Duas dicas de R | De Gustibus Non Est Disputandum

  3. The course is excellent! Here are the videos and slides from when I took the course in 2014: http://www.dataschool.io/15-hours-of-expert-machine-learning-videos/

  4. yjxie says:

    I am taking Tibshirani’s student’s data mining class this semester LOL He told me Tibshirani is really great.

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