A machine learning model created using Python that predicts the prices of houses in a specific area with 81% accuracy. Data was collected from Kaggle.com and was pre-processed using NumPy and pandas. Implemented several machine learning algorithms including linear regression, random forest regression and GridSearchCV using scikit-learn, in order to optimize results. View the jupyter notebook file to see a visualization of how the data was processed and the end results.