Enhancing Zillow Zestimates: Leveraging Machine-Learning for Precise Property Valuation Predictions

A variety of machine learning techniques, such as Linear Regression, Lasso Regression, Ridge Regression, Elastic Net, Decision Tree, Random Forest, and Gradient Boosting, are used in this work to evaluate the assessment of house worth. We want to improve the precision and dependability of house price forecasts by utilizing a variety of approaches. We compare how well these algorithms capture intricate correlations between different variables and home prices. By doing extensive testing and analysis, we aim to determine the best real estate value model, advancing predictive analytics in the housing industry. Our results will help buyers, sellers, and real estate agents make better-informed decisions.