Predicting Boston Housing Prices

Now that you've covered model evaluation and validation, it's time to get prepared for Project 1!

The Boston housing market is highly competitive, and you want to be the best real estate agent in the area. To compete with your peers, you decide to leverage a few basic machine learning concepts to assist you and a client with finding the best selling price for their home. Luckily, you’ve come across the Boston Housing dataset which contains aggregated data on various features for houses in Greater Boston communities, including the median value of homes for each of those areas. Your task is to build an optimal model based on a statistical analysis with the tools available. This model will then be used to estimate the best selling price for your clients' homes.

Project Files

For this assignment, you can find the boston_housing folder containing the necessary project files on the Machine Learning projects GitHub, under the projects folder. You may download all of the files for projects we'll use in this Nanodegree program directly from this repo. Please make sure that you use the most recent version of project files when completing a project!

Evaluation

Your project will be reviewed by a Udacity reviewer against the Predicting Boston Housing Prices project rubric. Be sure to review this rubric thoroughly and self-evaluate your project before submission. All criteria found in the rubric must be meeting specifications for you to pass.

Submission Files

When you are ready to submit your project, collect the following files and compress them into a single archive for upload. Alternatively, you may supply the following files on your GitHub Repo in a folder named boston_housing for ease of access:

  • The boston_housing.ipynb notebook file with all questions answered and all code cells executed and displaying output.
  • An HTML export of the project notebook with the name report.html. This file must be present for your project to be evaluated.

I'm Ready!

When you're ready to submit your project, click on the Submit Project button at the bottom of the page.

What's Next?

You will get an email as soon as your reviewer has feedback for you. In the meantime, review your next project and feel free to get started on it or the courses supporting it!