/boston-housing

Predicting Boston Housing Prices using Machine Learning

Primary LanguagePythonMIT LicenseMIT

Project Contents

This project contains the following files:

  • boston_housing.ipynb: Jupyter notebook containing project code.
  • housing.csv: The project dataset. You'll load this data in the notebook.
  • visuals.py: This Python script provides supplementary visualizations for the project.
  • boston_housing.ipynb: project notebook (Jupyter - Python 3.5)
  • report.html: A HTML export of the project notebook
  • project_discription.md: been provided with the project files which may contain additional necessary information or instruction for the project.
  • project_discription.md: Predicting Boston Housing Prices project rubric.

Requisites

Software and Libraries

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

You will also need to have software installed to run and execute a Jupyter Notebook

If you do not have Python installed yet, it is highly recommended that you install the Anaconda distribution of Python, which already has the above packages and more included. Make sure that you select the Python 2.7 installer and not the Python 3.x installer.

Data

This dataset is a modified version of the Boston Housing dataset found on the UCI Machine Learning Repository. It consists of 489 data points, with each datapoint having 3 features.

Features

  1. RM: average number of rooms per dwelling
  2. LSTAT: percentage of population considered lower status
  3. PTRATIO: pupil-teacher ratio by town

Target Variable

  1. MEDV: median value of owner-occupied homes

Code

Code is provided in the boston_housing.ipynb notebook file. It requires the included visuals.py Python file and the housing.csv dataset file to work.

Note that the code included in visuals.py is meant to be used out-of-the-box. If you are interested in how the visualizations are created in the notebook, please feel free to explore this Python 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

or

jupyter notebook boston_housing.ipynb

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

https://www.python.org/download/releases/2.7/