This paper was prepared by a first-year student pursuing Data Science and Business Analytics at the University of Warsaw's Faculty of Economic Sciences. The research was conducted as part of an unsupervised learning class led by Professor Dr. hab. Katarzyna Kopczewska. This project applies association rule mining to market basket analysis to uncover latent customer purchasing patterns and product co-occurrence structures. By integrating these insights with a strategic business lens, the analysis informs high-impact decisions in cross-selling, shelf placement optimisation, promotional bundling, and targeted merchandising to enhance revenue performance and customer basket value.

An end-to-end machine learning project implemented in R to predict heart disease using classification models. The workflow follows MLOps principles including modular code design, reproducible preprocessing, model evaluation, and REST API deployment using Plumber.

Red snapper