House Price Prediction by using Machine Learning

Abstract

The goal of this project is to create a machine learning model that can predict home selling prices by taking into account variables like location, square footage, number of bedrooms and bathrooms, and other relevant characteristics. The model prioritizes optimization for managing missing data in order to produce trustworthy estimates for the real estate market. This study advances real estate predictive modelling by using rigorous analysis and experimentation. It provides practitioners and stakeholders with useful information for making precise cost projections.