Στην παρούσα μελέτη, επικεντρωνόμαστε σε μια γραμμική παλινδρόμηση για την πρόβλεψη της τιμής πώλησης κατοικιών στο King County των Η.Π.Α.

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.

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