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Unformatted text preview: ISyE 7406 , Data Mining and Statistical Learning Spring 2009, MW 1:352:55 pm, IC 207 Professor: Kwok Tsui Office: 435 Phone: 894-2311 Email: email@example.com Website: www.isye.gatech.edu/people/faculty/Kwok Tsui Office Hours: MW 11:0012:00 pm; by appointment Text: The Elements of Statistical Learning by Hastie, Tibshirani, and Friedman, Springer Grading: Homework 10 %; Midterm 30 %; Project 60 %. Course Outline Topic Chapters Introduction to Data Mining 1 Supervised Learning 2 Linear Methods for Regression 3 Linear Methods for Classification 4 Model Assessment and Inferences 7 &amp; 8 Trees and Related Methods 9 Neural Networks &amp; SVM 11 &amp; 12 Forecasting Methods notes Unsupervised Learning 14 Case Studies notes Project An important objective in this course is to relate what you learn to real life problems, which will be achieved by working on a class project. Before you start working on your project, you need to discuss with the instructor in advance and submit a one-page proposal for approval. You areto discuss with the instructor in advance and submit a one-page proposal for approval....
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This note was uploaded on 11/13/2010 for the course ISE 680 taught by Professor Santanu during the Spring '10 term at Purdue University Calumet.
- Spring '10
- Data Mining