This repository contains projects written for a data mining class. They are roughly themed as follows:

1. project_1 - classifcation
2. project_2 - clustering
3. project_3 - recommendation systems
4. project_4 - regression

Here is an example from project 2, which shows the features of a dataset of 5 flowers extracted using an autoencoder. We then perform a compression by reducing the dimensionality from 4096 features to 50 via UMAP. Below is a projection of the resulting clusters:

1. Install Python 3.9 or higher.
2. Install all dependencies with pip install -r requirements.txt.
3. For any project, start up a jupyter server and open the .ipynb file.