Teams of students will complete a final project that applies some ideas from the class. Teams can consist of at most three students. Here are some guidelines:
- Your project shall be hosted on github. If you are on a team, pick one member's account.
- Add a link to your project's github repository here
- Add a descriptive README.md at the root of your project.
- You may use off-the-shelf analysis tools in your work; no need to start from scratch.
- Here are some projects from a CMU course that are good examples to help you come up with ideas.
- You must collect your own data for this project. You can get ideas of the types of data here.
The 200 points is broken down into:
- 10 points - Proposal: Is the proposal presentation clear, well-organized, and thorough?
- The proposal should be a 7 minute presentation (with 3-5 minutes for questions)
- A clear problem statement
- A clear hypothesis
- An overview of the method
- Specifics about the data you intend to use (how many, from where, with what attributes?)
- Description of how your project is similar to and different from related work
- A timeline for the remaining work. For teams, indicate who will do what.
- 40 points - Presentation: Is the presentation clear, well-organized, and thorough?
- 50 points - Code: Can I reproduce your results by running your code? Is the code well-written, debugged, and documented?
- 50 points - Report: Follow the similar format as the papers we read for class. Your report should be 5-6 pages, including all references and figures. Are the main algorithms, hypotheses, and assumptions clearly stated? Are the comparisons with related work sound? Sections include:
- Introduction: What did you do and why? What are the research questions of your analysis? What is your hypothesis?
- Data: What data did you collect and how?
- Methods: What did you do with the data, precisely?
- Experiments: These should answer your research questions and test your hypotheses.
- Related work: How have others approached this problem? What makes your approach different?
- Conclusions and Future Work: What should we have learned from reading your paper? What's left to do?
- 50 points - Scientific rigor: Are your claims supported by the experimental results? Have you attempted to rule out all other reasonable competing hypotheses? Are the experiments soundly developed and executed?