CS539 Machine Learning
Syllabus— Fall 2015
For the catalog description of this course see the WPI Graduate Catalog.
Time: Tuesdays and Fridays 3:00-4:20 pm
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, Quizzes, and Final ExamThere will be 3 homework assignments, 2 quizzes, and a final exam.
Students' mastering of the material in HW1 (resp., HW2 and HW3) will be tested in Quiz1 (resp., Quiz2 and Final Exam). The final exam will be cumulative and will test the students' mastering of the material covered in the entire course.
Detailed descriptions of the HW assignments will be posted to the course webpage at the appropriate times during the semester.
ProjectsThere will be a total of 2 projects. These projects will include implementation, experimentation, and analysis of results. The projects may include also assigned readings and theoretical problems. In each project, students will work individually during the first stage of the project and then in assigned teams. Students will be required to provide both a written report and an oral (in-class) presentation describing their work on each of these projects. Both individual and group work will be graded.
Detailed descriptions of the 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.
Please make sure to read myWPI CS539 forums and email sent to the class mailing list constantly throughout the semester so that you don't miss any important course information.
The webpages for this class are located at http://www.cs.wpi.edu/~cs539/f15/
Announcements will be posted on the web pages and/or the class mailing list, and so you are urged to check your email and the class web pages 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.