General Information
To fulfill the independent work requirement of the CSML undergraduate certificate, the project must have a substantial machine learning or statistics component. Typically, this is achieved in one of two ways: via applied work or via a core methodological contribution.
Applied projects should tackle some domain of intellectual interest in science, engineering, the humanities, etc. The project should use machine learning or statistical methods in a non-trivial way to analyze the data or in support of an engineering goal. The project report should go into detail about what these methods were and how they were used.
Methodological or theoretical projects will push forward our understanding of machine learning or statistical techniques. Such projects may propose new models, optimizers, inference approaches, estimators, etc. In this case, the report will primarily serve to explain the idea and then evaluate it empirically and/or theoretically. The main results of such a project may be theorems or comparisons against alternative techniques.
Presentation of the project at the CSML IW poster session is required.
Important Dates
- February 20, 2023 by EOD – Tentative title and abstract due and uploaded into Canvas - will be reviewed by faculty. Any comments or guidance will be relayed to you, if necessary.
- May 4, 2023 – All work due and should be uploaded to Canvas. Final title/abstract, independent work paper and video (2-5 min video) all due in Canvas.
Independent Work FAQ
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Can I use my JP or senior thesis from another department for my CSML IW?
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Yes, you can. As long as the project has a substantial machine learning or statistics component to it, you may submit work that was done for another program.
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I’m working with a graduate student in a lab on a collaborative project. Can I use that project for my CSML IW?
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Yes, you can use such a project as the basis of your CSML IW. However, you should report on your own work in support of the project, and what you did yourself should have a substantial machine learning or statistics component to it.
Independent Work Poster Information
For the 2023 CSML Poster Session, you will need to submit your assignments and engage in discussions with your fellow students through Canvas.
Instructions for submitting your work.
Please see below the poster requirements as well as past poster winner examples. If you have questions, please email [email protected]
- size: 36" x 24"
- format: PDF, JPG (powerpoint and keynote files are not acceptable.)
Examples of previous work
For more information on when these submissions are due, please review the dates at the top of this page. If you have any questions, please email [email protected]