Course Information for Spring 2013
Time: MWF 9:00-9:50
Place: Roberts 221
Final exam: Sunday, May 19th, 9:00 am
Instructor Information
Prof. Stephanie R. Taylor (Lectures)
Office: Roberts 224D
Email: s r taylor _at_ colby _dot_ edu
Office hours: M 1:30-3:30, T 2-5, F 1-3
By appointment (email me), and whenever my door is open
Prof. Bruce Maxwell (Labs)
Office: Roberts 224B
Email: b maxwell _at_ colby _dot_ edu
Office hours: knock
Bruce is on AIM (see lab page for address) and is happy to be contacted whenever he is logged on
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
- Lighthouse International's Page on making design accessible to the visually impaired
- 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