Comprehensive Real Estate Dataset for Predictive Modeling and Price Forecasting

This dataset, originally published as part of a public data science competition on a leading machine learning platform, contains detailed records of residential homes in Ames, Iowa. It includes 79 explanatory variables describing various aspects of the properties, such as location, size, construction materials, and neighborhood characteristics, along with the target variable—sale price. The dataset is widely used for regression modeling and machine learning experiments focused on real estate price prediction. Disclaimer: This dataset is sourced from an open data science platform and is provided here strictly for educational and non-commercial research purposes. All rights and original credits belong to the dataset creators and the original platform. Users are advised to review the original license and usage terms before applying the data in any commercial or derivative projects.