An important part of the learning experience associated with this course (and 40% of the grade) comes from experimenting with the algorithms presented in class. This page describes what is expected from the students. Feel free to ask questions below.
Objectives
- Get hands-on experience with some of the algorithms presented in the course.
- Practice the writing of an experimental journal (e.g. on a blog dedicated to your experiments for this course), describing your ideas, experimental plans, experimental results, and discussions of potential conclusions (i.e., the stuff that eventually ends up in papers).
- Practice the use of collaborative tools for writing code, using a repository dedicated to your experimental work (e.g., with Github).
- Practice the collaborative competition typically enjoyed by scientists:
- Work of each student (in the code repository and in the blog) is available to the others to build upon, thus speeding up the overall rate of progress of the group.
- Each student is encouraged to re-use the ideas, results, tricks, and code from other students but MUST properly cite and acknowledge these inputs (plagiarism without citation will be severely punished).
- Each student competes to obtain good results on common benchmarks, but can take advantage of the good ideas of the others, hence the collaborative competition.
- Students are encouraged to keep track (in their blog) of the uses by other students of their contributions (to make sure they get points for that), and to talk to each other when one notices that another one is using someone else’s idea or code without attributing credit, or report the case to the instructor or his assistant.
Requirements
- Maintain a blog detailing ideas, experiments and progress. Some periods of the semester may be more active than others, but an average of one blog post per week is the minimum required.
- Make your code publicly available through a Github repository.
Part of the grade will come from having been the first to do something useful and publicize it on your blog (possibly posting here announcements with links to the blog). The more this contribution is useful to advancing each other’s progress, the more points will be given. This should provide an incentive to do things quickly that may otherwise look boring but that could be useful to others.
(project-specific details will be added later)
Blogs and repos
Please start by creating your blog and your code depository. A list of pointers to these will be maintained below.
Some examples from previous years
- Laurent Dinh
- Vincent Dumoulin
IFT6266 H-2016 Deep Learning 