Overview
An integral part of the course is the class project, which gives students a chance to apply the algorithms discussed in class to a research-oriented problem. You may use a dataset available on the web or collect your own data. If you choose to collect your own data, remember that data collection is often more time-consuming than expected.
The complexity and ambition of the project topic will be taken into consideration during grading.
Software and libraries
You are encouraged to use appropriate machine learning and deep learning tools for your project. Useful starting points include:
Deliverables
- Project proposal · 23 October
- Project progress report · 8 December
- Final project presentation · 22 December
- Final report and code · 31 December
Progress and final reports should use the provided LaTeX template and be submitted electronically in PDF format. Late submissions will be penalized according to the policy announced during the semester.
Collaboration policy
Each project should normally be completed in pairs. Exceptions may be made depending on enrollment. Students without a team may be assigned to a project group.
Grading
- Proposal: 3%
- Progress report: 10%
- Presentation: 10%
- Final report and code: 12%
Project proposal
Each project group should submit a proposal that clearly identifies:
- The research topic to be investigated.
- The main challenges that will be faced.
- The data that will be used.
- A short, contextualized list of related papers.
Progress report
The progress report should be 5 pages + references and describe the problem, related work, the methodology being used, the experimental setup, and any preliminary results. It should make clear how the project will be evaluated and which datasets and metrics will be used.
Project presentations
Each group will give a short in-class presentation, including questions and answers. A strong presentation should cover the problem and motivation, the key technical ideas, the experimental setup, the main results, and a candid discussion of strengths and weaknesses.
Final report
The final report should be 9 pages + references and structured as a research paper. A typical organization is:
- Title and authors
- Abstract
- Introduction and motivation
- Related work
- Approach
- Experimental setup and results
- Conclusions and possible future work
- References