General Info

CPSC 599.44: Machine Learning - Assessment

The University policy on grading and related matters is described in the university calendar.

The course will not have a Registrar's scheduled final examination, but will have a final oral exam during the exam period, which is one of two components that are done by students individually. The other component is a report by each student on the system and the created learning results that his/her student team produced.

Naturally, this system has to be developed and implemented and this will be the major team component of the course. Additionally, the team component includes a midterm report about the plans the team has for this system, especially what learning method to use and what application specific instantiations/modifications the team plans to do.

The following table describes the percentages with which the grades for the components above will be weighted to compute the final grade of a student.

Final Oral Exam        40%
Individual system report        15%
Team report on plans for system        15%
Implemented learning system        30%

Each of the items above will be graded individually and then I use the percentages to get the final grade. So, if, for example, a student got an A- in the Final, an A for the system report, and his/her team got a B for the system and the report on the plans, then we have (3.7*4 + 4.0*1.5 + 3.0*3 + 3.0*1.5)/10 = 3.43, which will be rounded to 3.3 (i.e. B+).

Please note that in order to pass the course, you have to achieve a passing grade in the weighted combination of individual system report and final exam!

to the materials for the course.

Last Change: 14/5/2019