A data science and machine learning project analyzing Istanbul housing listings to uncover the factors that influence real estate prices and build a predictive pricing model. The project covers data cleaning, exploratory data analysis, statistical hypothesis testing, feature engineering, and regression modeling.

Cleaned and preprocessed real-world housing data

Performed exploratory data analysis and visualized key pricing patterns

Engineered features for predictive modeling

Conducted statistical hypothesis tests, including t-tests, ANOVA, and Mann–Whitney U tests

Built and evaluated regression models for real estate price prediction

Analyzed relationships between property characteristics, location, and listing prices

Python

Pandas

NumPy

Scikit-learn

Matplotlib

SciPy

Jupyter Notebook