We will closely follow the excellent recent book "Machine Learning" by Tom M. Mitchell and will discuss several state of the art research articles. The course will provide substantial hands-on experience through four computer projects. These projects use code and datasets provided online as companions to the textbook.
For the catalog description of this course see the WPI Graduate Catalog.
Thursdays 6:00-8:50 pm
Students are also encouraged to attend the KDDRG Seminar Fridays at 2:00 pm.
Prof. Carolina Ruiz
Office: FL 232
Phone Number: (508) 831-5640
Office Hours: Mo 11:00-12:00 m, Th 3:00-4:00 pm, or by appointment.
Other speakers may occasionally be invited to lecture to the class.
CS 534 or equivalent, or permission of the instructor.
|Weekly Assignments||80% (8% each)|
|Class Participation||Extra Points|
Your final grade will reflect your own work and achievements during the course. Any type of cheating will be penalized with an F grade for the course and will be reported to the WPI Judicial Board in accordance with the Academic Honesty Policy.
Projects that involved developing code may be implemented using any high level programming language (Lisp, Prolog, C, C++, ...) The code you submit for each of the projects should run on the WPI CS machines or the CCC machines and should rely on software available on those machines only.
More detailed descriptions of the assignments and projects will be posted to the course webpage at the appropriate times during the semester. An in-class presentation of each of the assignments will be required.