Real Estate Price Prediction using ANN

Abstract

This report explores the use of machine learning to predict real estate prices, addressing challenges such as market dynamics and data complexity. Through extensive data analysis and feature engineering, the study implements decision trees, random forests, and neural networks to capture the intricate factors affecting property values. The performance of these models is rigorously evaluated, providing stakeholders with reliable forecasts and insights into key price determinants. This research enhances decision-making in the real estate sector by improving the accuracy and transparency of price predictions. A Graphical User Interface is also developed to enter required information and display the predicted price. Keywords—Machine Learning, Price Prediction, Artificial Neural Network