This project was created by Marios Apostolidhs as part of a university assignment for the Business Analytics course. It explores a real estate dataset from King County (USA) and applies linear regression techniques to analyze and predict house prices. The work includes basic data cleaning, visualization, and the development of both simple and multiple linear regression models. It’s a hands-on attempt to apply what we learned in class to a real-world dataset.

test

dashboard

Este análisis explora un conjunto de datos de vinos utilizando Análisis de Componentes Principales (PCA) y Escalamiento Multidimensional (MDS) para identificar patrones y diferencias entre los vinos. Se incluyen visualizaciones interactivas y agrupamiento mediante clustering.