Navigating Bangalore's Real Estate: A Study Based on a Novel Property Price Dataset

This paper presents an encompassing analysis of property price prediction using three different ML algorithms: Multi Linear Regression (MLR), Random Forest (RF), and XGBoost(XGB). The study utilizes a novel dataset - Bangalore Property Valuation Data comprising various property features to train and evaluate the models for accurate price estimation. This study fosters investor confidence and facilitates efficient allocation of resources within the economy. This study's outcome and results contribute to the advancement of property price prediction methodologies, enabling stakeholders to make more informed decisions in real estate transactions and investment strategies. The research contributes valuable insights into lever-aging machine learning techniques for property price prediction and offers a roadmap for future research in this domain.