Average full-time adjusted salaries per employee in Greece -in red-\ncompared with EU countries (source: Eurostat)

This project explores predicting obesity levels using demographic, lifestyle, and physical attributes. Four machine learning models were applied: Multinomial Logistic Regression, Decision Trees, Random Forests, and K-Nearest Neighbors. Their performance was evaluated using confusion matrices and accuracy scores. Random Forest achieved the best overall performance, while Logistic Regression offered strong interpretability. The study highlights the potential of machine learning in classifying obesity levels and guiding health-related decision-making.

Bootcamp statistics homework

IMB Bootcamp 2025

A dynamic Shiny application and reproducible pitch for exploring the mtcars dataset, created for the Developing Data Products course project.

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