The analysis of data (DNA microarrays, music, images, video, financial records, web logs, medical records, software, computer game logs, motion capture in graphics) is an important frontier in computer science. This frontier is expanding vastly thanks to new developments in storage devices and the world-wide web. This course will teach the basic principles and skills required for analysing data: finding patterns, dimensionality reduction, clustering, classification and prediction.

Time: Mon Wed Fri 16:00-17:00

Location: Geography 200

Instructor: Nando de Freitas (nando at cs)

Nando's Office hours: W 2:00-3:30 (cicsr 183).

TAs: Rita Sharma ( rsharma at cs) and Hendrik Kueck ( kueck at cs).

Rita's TA hours: Th 1:00-2:00pm (cicsr 235)

Text book: The elements of Statistical Learning.

Other books

Pattern Classification.

Principles of Data Mining.

Modeling the Internet and the Web.

Grading

Assignments: 20%

Midterm 1: 30%. Oct 22.

Final: 50%

There will also be a special research project for advanced students.

The instructor has the right to change the marking scheme under reasonable circumstances.

Assignments

Assignments will involve both written and matlab programming problems.

The handin box is located in the CICSR/CS building (basement floor).

All assignments are due on the specified time. 20% off for each day late. Assignments will not be accepted after 5 days late.

Newsgroup: ubc.courses.cpsc.340