EMTM 554: Data Mining

What is data mining? The data mining process. Data visualization. Data mining methods: decision trees, regression, neural nets, clustering, network analysis and feature selection. How the methods work. When to use them. Evaluation of business intelligence systems. Privacy issues in data use. Strategic use of information. Emerging data mining methods: text mining. This is a technical elective and will go into detail on the various methodologies, as well as looking at current industry trends. Prerequisite: Statistics and knowledge of JMP.

Administrivia

Course Syllabus
Homework
Textbook
- Data Mining Concepts and Tecnhiques second edition (Han and Kamber)
Professor
- Lyle Ungar (ungar@cis.upenn.edu)
WebCafe
Quiz sample problems and solutions
References
Data sets See in particular the KDD cups and the UCI repository
Software The Course will use JMP.
Grades (by last 3 digits of Penn ID)
- 25% based on the final quiz
- 50% based on homework other than the final project
- 25% based on the final project

Announcements

Pre-assignment due the first day of class is posted as hw1 under the "Homework"

This page is http://www.cis.upenn.edu/~ungar/DBM/

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ungar@cis.upenn.edu