Final Project
UQ MATH7502
Mathematics for Data Science 2 (2020)

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The final project is to be submitted individually. However, each project may have up to two named advisors where a minimum of one advisor per project is recommended. These advisors are to give you tips and feedback on your project dealing with the mathematical content, the software, the presentation, and the use of language. It is recommended that in addition to working on your project, you serve as an advisor to one or two other projects (you may advise a maximum of three projects). It is recommended to seek advisors early on during the semester. If you are strong in A and weak in B, seek advisors in B and offer your advise with A.

Plagiarism will not be tolerated. There is a clear difference between receiving advise and copying the work of others. The voice recording submitted with the project will describe the advise received.

Your project submission should have demonstrations for 3 out of these 6 topics appearing in [DSUC]: Topic 2 (perceptron), Topic 4 (classification), Topic 5 (multi-objective and regularization), Topic 9 (Gaussians weighted least squares), Topic 11 (gradient descent), and Topic 12 (PCA).

Each presentation will involve a stylized Jupyter notebook involving formulas, text, data, figures, and code. The presentation will also involve a video. Exact instructions for the presentations and the topics will be supplied by week 9.

A full description of the project is here.