Machine Learning

Grading

The grading for this class will comprise of the following continuous assessment milestones and a final assessment. The final exam will be open book, but the midterm is closed book. Both the midterm and final assessment will largely be MCQ/MRQ based.

This module is a flipped module, meaning that most lectures (with the exception of Weeks 1, 7 and 13) are online and done at your own pace through watching the appropriate pre-recorded videos. For Weeks 1, 7 and 13, you must be in class during the classroom hours. Staff contact will be mostly conducted through Tutorials and Project Consultations (to be arranged individually per project group).

Lecture and tutorial attendance is not mandatory, but will help with your participation grade. Participation is very helpful for your teaching staff too. Without it, we have very little idea whether you understand the material that we’ve presented or whether it’s too difficult or trivial. Giving feedback in the form of questions, discussion provides us with a better idea of what topics you enjoy and which you are not too keen on.

Academic Honesty Policy

Please note that we enforce these policies vigorously. While we hate wasting time with these problems, we have to be fair to everyone in the class, and as such, you are advised to pay attention to these rules and follow them strictly.

Collaboration is a very good thing. Students are encouraged to work together and to teach each other. On the other hand, cheating is considered a very serious offense. Please don’t do it! Concern about cheating creates an unpleasant environment for everyone. You will be automatically reported to the vice-dean of academic affairs if you are caught, no exceptions will be made for any infractions no matter how slight the offense.

So how do you draw the line between collaboration and cheating? Here’s a reasonable set of ground-rules. Failure to understand and follow these rules will constitute cheating, and will be dealt with as per University guidelines. We will be enforcing the policy vigorously and strictly.

You should already be familiar with the University’s honor code. If you haven’t yet, read it now.

The Pokémon Go Rule: This rule says that you are free to meet with fellow students(s) and discuss assignments with them. Writing on a board or shared piece of paper is acceptable during the meeting; however, you may not take any written (electronic or otherwise) record away from the meeting. This applies when the assignment is supposed to be an individual effort. After the meeting, engage in a half hour of mind-numbing activity (like catching up with your friends and family’s activities on Facebook, before starting to work on the assignment. This will assure that you are able to reconstruct what you learned from the meeting, by yourself, using your own brain. The Freedom of Information Rule: To assure that all collaboration is on the level, you must always write the name(s) of your collaborators on your assignment. Failure to adequately acknowledge your contributors is at best a lapse of professional etiquette, and at worst it is plagiarism. Plagiarism is a form of cheating.

The No-Sponge Rule: In intra-team collaboration where the group, as a whole, produces a single “product”, each member of the team must actively contribute. Members of the group have the responsibility (1) to not tolerate anyone who is putting forth no effort (being a sponge) and (2) to not let anyone who is making a good faith effort “fall through a crack” (to help weaker team members come up to speed so they can contribute). We want to know about dysfunctional group situations as early as possible. To encourage everyone to participate fully, we make sure that every student is given an opportunity to explain and justify their group’s approach.

This section on academic honesty is adapted from Surendar Chandra’s course at the University of Georgia, who in turn acknowledges Prof. Carla Ellis and Prof. Amin Vahdat at Duke University for his policy formulation. The origin of the original rule, called the Gilligan’s Island rule, is uncertain, but at least can be traced back to Prof. Dymond at York University’s use of it in 1984.

Late Submissions

All homework assignments are due to Coursemology by 23:59:59 (Singapore time) on the due date. No exceptions without a medical certificate will be made. The following penalties will apply for late submissions:

• late within 1 hour: 10% reduction in grade;
• late within 5 hours: 30% reduction in grade;
• late within 1 day: 50% reduction in grade;
• late within 5 days: 70% reduction in grade;
• after 5 days: zero mark.

These penalties are intentionally set severe to encourage students to turn in assignments on time. This in turns, means that your teaching staff can start and finish grading within a certain time period, and can help you get timely feedback on your work. Do not expect any type of preferential treatment if you turn in an assignment late.

Assignment return policy and regrades

All students have a right to question the grading of their work. If a regrade is sought for a particular milestone, this must be brought to our attention within 3 days of the return of the preliminary grades by email. Requests later than that will not be entertained without certified medical leave or school permission.