Multiple Linear Regression

We have already covered regular linear regression, as well as linear regression with polynomial terms, and considered training them with both the least squares method and gradient descent. This section of the chapter will consider an additional type of linear regression: multiple linear regression, where more than one type of variable (or feature) is used to construct the model. To examine multiple linear regression, we will use a modified version of the Boston Housing Dataset, available from https://archive.ics.uci.edu/ml/index.php. The modified dataset can be found in the accompanying source code or on GitHub at https://github.com/TrainingByPackt/Supervised-Learning-with-Python and has been reformatted for simplified use. This dataset contains a list of different attributes for property in the Boston area, including the crime rate per capita by town, the percentage of the population with a lower socio-economic status, as well as the average number of rooms per...