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"Buying a house is a stressful thing." We built a model to predict the prices of residential homes in Ames, Iowa, using advanced regression techniques. This model will provide buyers with a rough estimate of what the houses are actually worth. We first analyzed the data to find trends. Then dimensionality reduction was performed on the dataset using PCA algorithm and feature selection module in sklearn package for python 3.5. The final house prices are predicted using linear regression models like Ridge and Lasso. We also utilised advanced regression techniques like gradient boosting using XGBoost library in python 3.5.