CS539 Machine Learning
Syllabus— Spring 2017
For the catalog description of this course see the WPI Graduate Catalog.
Time: Tuesdays and Thurdays 4:00-5:20 pm
Prof. Carolina Ruiz
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.
Note that this course follows the guidelines established by the WPI faculty in May 2010:
"A student is expected to expend at least 56 hours of total effort for each graduate credit. This means that a student in a 3-graduate credit 14-week course is expected to expend at least 12 hours of total effort per week."Hence, please expect to have to spend at least 9 hours of work outside the classroom on this course each week.
Students are expected to read the material assigned for each class in advance and to participate in class discussions. Class participation will count toward students' final grades.
HOMEWORK ASSIGNMENTS, TESTS, AND PROJECT
Homework Assignments and TestsThere will be 4 homework assignments and 4 tests:
Detailed descriptions of the HW assignments will be posted to the course webpage at the appropriate times during the semester.
ProjectThere will be one course project. This project will include data acquisition, experimental design, programming, experimentation, and analysis of results. The project may also include assigned readings and theoretical problems. Students will be required to provide both a written report and an oral (in-class) presentation describing their work on the project.
A detailed description of the project will be posted to the course webpage at the appropriate time during the semester.
Programming Language / Environment: MatlabFor the homework assignmens, tests, project, and class demos, we will use Matlab. Matlab is available at WPI on specific computer labs around campus AND/OR via the remote desktop connection to windows.wpi.edu. A link to instructions about the remote desktop connection can be found at https://it.wpi.edu/component/id/77.
Note: only Matlab support will be provided in this course. Individual students may petition using R instead of Matlab for their project, but they will be fully responsible for dealing with R as all class demos, homework, and tests will use Matlab.
The webpages for this class are located at http://www.cs.wpi.edu/~cs539/s17/
Announcements will be posted on the web pages and/or the class mailing list and/or the Canvas discussion forums, so you are urged to check Canvas, your email and the class webpages frequently.
Small changes to this syllabus may be made during the course of the semester.
Machine Learning, AI, Data Mining, Statistics, Databases, Data Sets and other online resources.