If you are taking CS 446 for 4 hours credit, you need to do a research project. We have provided templates for the initial proposal, intermediate report, and final report. These templates should help guide you as you work on your project over the course of the semester. In particular, you should work on the Introduction, Background, Task, and Data sections before you implement your system and run your own evaluations. Note that you cannot perform any machine learning experiments without having suitable test and training data, or knowing what to evaluate.
Project deadlines: TBA
We will not have any oral presentations on the projects. You will be graded on your written reports, which you will submit through Compass.
Proposal templates: (.tex and .pdf)
In your initial proposal, you should provide a summary of your chosen project. This includes a description of the task and a brief review of prior work, as well as explaining your intended approach and the datasets you will use to train and evaluate your system. Finally, you need to provide a to-do list breaking your project into sub-tasks with projected deadlines.
Intermediate report templates: .tex and .pdf)
By the time your intermediate report is due, you are hopefully close to a state where you can soon run your final experiments. At the very least, you should have your data and some code set up by now. The template for the intermediate report is almost identical to the final report, except it contains a to-do list at the end. Do not fret over presentation at this point. It's intended as a checkpoint to make sure you're making progress, but this does not have to be a polished report. Look at the timeline/to do list that you set up for your initial report: what have you done, what is left to do? Give us a new, updated timeline. Report any experimental results you already have.
Final project report templates: .tex and .pdf)
Your final report is the culmination of your course project, and its quality should reflect the amount of work you have dedicated over the course of the semester. We recommend that you use the provided template to guide your efforts; completing the background work and task description will provide a solid base for the rest of your project.
We will not follow any particular textbook. All the books listed below are reserved in the Engineering Library. If you plan to do research in Machine Learning or related areas you will eventually need some of these books; otherwise, borrowing a copy is sufficient for now.