• DHANVISHYAM U B
• Dr. Shashidhar Kini K

This study undertakes the development of a Property Price Estimator for the Bangalore residential real estate market using machine learning regression models. To predict property prices, key features derived from property listings are used. These features include location, size, number of bedrooms, bathrooms, and property type. For this purpose, contemporary cross-sectional data was scraped from Indian real estate portals (Makaan.com, Commonfloor.com). The analytical framework involves data collection, preprocessing, feature analysis, and the training and evaluation of predictive models like Linear Regression and XGBoost.

Property Price Prediction, Machine Learning, Regression Analysis, XGBoost, Linear Regression, Data Scraping, Real Estate Analytics, Bangalore Housing Market

"PROPERTY PRICE ESTIMATOR USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 7, page no.1129-1132, July-2025, Available :http://www.jetir.org/papers/JETIRGX06216.pdf

"PROPERTY PRICE ESTIMATOR USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 7, page no. pp1129-1132, July-2025, Available at : http://www.jetir.org/papers/JETIRGX06216.pdf