Course Information for Spring 2012
Time: MWF 8-8:50am Lecture, M 1-2:15/2:30-3:45 Lab
Place: Roberts 221/228
Instructor Information
Prof. Bruce A. Maxwell
Office: Roberts 224B
Phone: 859-5854
AIM: brucemaxwell@mac.com
Office hours: Knock
Course Description
This course covers the analysis and visualization of scientific data. Topics will include data management, basic statistical analysis, data mining techniques, and the fundamental concepts of machine learning. Students will also learn how to visualize data using 2-D and 3-D graphics, focusing on techniques that highlight patterns and relationships. Course projects will use data from active research projects at Colby.
Textbooks
Witten and Frank, Data Mining: Practical Machine Learning Tools and Techniques, Morgan Kaufmann, 3rd Ed, 2011.
Useful Links
- Maxwell's Lecture notes
- Course Wiki
- BirdVis paper
- Microsoft Kinect paper on pose recognition using decision trees
- Good and bad examples
- Python website
- Safari Online College Resources
- Weka machine learning software
- Visualization Examples
- 175+ Data and Information Visualization Examples
- Analysis and Critique of Visualization
- Example of an interactive visualization tool by Hans Rosling
- Bayes example data set
