The goal of the last Homework is to pick a dataset of your choice and analyse it with non-trivial algorithms, leading to interesting conclusions and/or observations about the dataset. The algorithms can be taken from this year's course, but not necessarily limited to them.
This dataset can be original (i.e. created by yourself as part of the hw) or taken from somewhere else (e.g. from a Kaggle challenge). For ideas, you can refer to Moodle branch “Sample datasets for the final projects”, where you will find links to interesting datasets.
You are encouraged to be creative, both in the choice of the dataset and the analysis performed on it. `Fun' and `realistic' topics are equally welcome. Once you have a project idea, you must first submit it on Moodle (branch “Dataset submission”). We shall then approve it or suggest changes. Once it is approved you can start working on it.
Please describe your dataset briefly (what it's about, size, where did/will you find it) and the kind of analysis you wish to perform (type of algorithms, type of conclusions, why it's interesting). It doesn’t have to be long, just enough for us to provide feedback/advice on feasibility and suitability for the project. It's not a 'contract', it doesn't commit you to do exactly what you announced.
The final product will be a written report of maximum 10 pages, and a short 5-mins oral presentation.
