Property Price Prediction

This research aims to predict real estate prices in Bosnia and Herzegovina using a dataset sourced from an online marketplace specializing in property listings. Methodologically, it employs the Random Forest algorithm for predictive modeling and conducts comprehensive exploratory data analysis (EDA) to uncover insights into property categories, feature correlations, and temporal trends. The dataset comprises over 10,000 real estate listings, with data cleaning, EDA, and feature engineering forming the foundation. Anticipated outcomes include a robust predictive model, insights into feature importance, and a nuanced understanding of temporal trends impacting property prices. Limitations may arise from reliance on scraped data and potential biases in online listings, necessitating continuous model validation and refinement to mitigate these challenges.