Welcome to Boston Massachusetts in the 1970s! Imagine you're working for a real estate development company. Your company wants to value any residential project before they start. You are tasked with building a model that can provide a price estimate based on a home's characteristics like:

• The number of rooms

• The distance to employment centres

• How rich or poor the area is

• How many students there are per teacher in local schools etc

Today you will:

1. Analyse and explore the Boston house price data

2. Split your data for training and testing

3. Run a Multivariable Regression

4. Evaluate how your model's coefficients and residuals

5. Use data transformation to improve your model performance

6. Use your model to estimate a property price

Download and add the Notebook to Google Drive

As usual, download the .zip file from this lesson and extract it. Add the .ipynb file into your Google Drive and open it as a Google Colaboratory notebook. All of today's challenges and explanations are contained in the notebook itself.

Add the Data to the Notebook

The .zip file also includes a .csv file. This is the data for the project. Add this file to your notebook.