This project evaluated the performance and predictive power of a model that has been trained and tested on data collected from homes in suburbs of Boston, Massachusetts. A model trained on this data that is seen as a good fit could then be used to make certain predictions about a home — in particular, its monetary value. This model would prove to be invaluable for someone like a real estate agent who could make use of such information on a daily basis.
The dataset used in this project is included with the scikit-learn library (sklearn.datasets.load_boston). You do not have to download it separately. You can find more information on this dataset from the UCI Machine Learning Repository page.