Predicting Boston Housing Prices

Supervised Learning: Model Evaluation & Validation

Install

This project requires Python 2.7 and the following Python libraries installed:

• NumPy
• matplotlib
• scikit-learn

You will also need to have software installed to run and execute an iPython Notebook

It is recommended to install Anaconda, i pre-packaged Python distribution that contains all of the necessary libraries and software for this project.

Code

Source code is in the boston_housing.ipynb notebook file.

Run

In a terminal or command window, navigate to the top-level project directory boston_housing/ (that contains this README) and run one of the following commands:

ipython notebook boston_housing.ipynb jupyter notebook boston_housing.ipynb

This will open the iPython Notebook software and project file in your browser.

Data

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.