Given a transaction dataset, I was tasked to find the most common set of items purchased together.
There were two key approaches. The first was a simple correlation analysis to find the most common pairs of products.
To extend this to finding groups of larger than two products, I implemented a graph to find groups of varying sizes to determine a list of products that are commonly purhcased together.
Used data from https://archive.ics.uci.edu/ml/datasets/online+retail to perform Customer Segmentation. Analysis utilizes RFM Analysis and Clustering (K Means, Hierarchical Clustering, and Gausian Mixture Models).
These projects were developed in Java and utilized the model-view-controller (MVC) design pattern.
- Tetris
Developed a Tetris game that can be run in an executable JAR file. Game has multiple levels where the speed of blocks falling speeds up as the user clears more rows.
- Twenty Questions
