House Prices Prediction

Background: Understanding factors influencing house prices is crucial in real estate markets. This study aims to identify key determinants affecting house selling prices.

Objectives: Investigate the significance of lot area, living space, house quality, construction year, basement exposure, heating and air conditioning types, fireplaces, garage capacity, wooden floors, and porch size on house prices. 

Methods: Employed EDA and machine learning algorithms on housing dataset. Developed regression models to quantify relationships between variables and prices.

Results: Found lot area, living space, quality, construction year, basement exposure, heating, air conditioning, fireplaces, garage capacity, wooden floors, and porch size as significant factors, explaining 87% to 89.6% of price variability.

Conclusion: Insights aid real estate stakeholders in making informed decisions regarding property investments and transactions.

See the full project at https://github.com/georgeoiko3/Personal-Projects/blob/main/Pj2-Report.pdf