Course Information for Spring 2015
Time: MWF 9:00-9:50
Place: Lovejoy 215
Final exam: Sunday May 17, 2015 at 6pm (Exam Period 15)
Instructor Information
Prof. Stephanie R. Taylor (Lectures)
Office: Davis 114
Email: s r taylor _at_ colby _dot_ edu
Office hours: Monday 1:30-3:30, Tuesdy 2-5, Thursday 1-3
By appointment (email me), and whenever my door is open
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.
Recommended Textbook
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
- Microsoft Kinect paper on pose recognition using decision trees
- Good and bad examples
- Python website
- Visualization Examples
- 175+ Data and Information Visualization Examples
- Analysis and Critique of Visualization
- Example of an interactive visualization tool by Hans Rosling