Instructor: Harrison H. Zhou
TA: Peisi Yan
Class Time: Monday and Wednesday11:35-12:50PM in Room 107, 24 Hillhouse Ave (Statistics department building)
Course Description: Techniques for data mining and machine learning are covered from both a statistical and a computational perspective, including support vector machines, bagging, boosting, neural networks, and other nonlinear and nonparametric regression methods. The course will give the basic ideas and intuition behind these methods, a more formal understanding of how and why they work, and opportunities to experiment with machine learning algorithms and apply them to data.
The Element of Statistical Learning by Hastie, Tibshirani and Friedman (online version available)