FAQIntroduction to Machine Learning - 10-701/15-781
Practical information
Office hours and questionsIf you have questions, you should do the following:
GradingHomework, midterm, and project count 33% each. You can pick the best two out of three for grading (translation, you can flunk one and still get full points). Moreover, the final exam counts 34% and it is mandatory. AuditingTo satisfy the auditing requirement you must do one of the following:
Please send an email to the instructors that you'll be auditing the class and let them know beforehand what you're planning to do. Waitlisted studentsIf you are waitlisted do not despair. Often students drop out and you will get a slot eventually. If there's space in the lecture theater, feel free to attend (obviously students who are registered have priority). Also, the videos of the lectures will all be up online, typically within 24-48 hours of the class (the exact timing depends on compression, network speed, and the time it takes YouTube to process the videos). To ensure that you can get credits for your homework, you need to do the following: do the assignments and put them into a dated and sealed envelope with your name on it. Write waitlisted on the envelope. We will open and grade the assignments only once you are no longer waitlisted. There is no guarantee that we ever will do that. It will only happen if you are officially enrolled. That said, students who diligently submit assignments will get priority over students who don't. If you're still waitlisted by the time of the midterm, it's too late. Assignments
ExamsThere are two exams. The midterm exam is on Monday, March 4, 2013. The final exam is on Monday, May 6, 2013, both of which are in lieu of the regular class. ProjectLike any class project, it must address a topic related to machine learning and you must have started the project while taking this class. You will need to submit a project proposal (i.e. a paper draft) and present a poster. You need to present a final paper and a poster. The 6 best projects will get the opportunity to give brief talks about your work at the end of the class. The rest gets spotlights. The final project should be completed in teams of 3 students. Teams of 2 or 4 are OK if there’s a good reason. Obviously, larger teams are expected to deliver more. Single projects are not OK unless you can prove that a) nobody would take you on their team and b) there is no project that you would like to work on. In an emergency, Alex and Barnabas can help overcome obstacles a) and b). The report should describe the project. It should describe your work in a reproducible manner, i.e. in enough detail that someone competent could take the report and regenerate the results (after some work but no guesswork) reliably. |