Standardizing the features

Standardization is the process of centering the variable at zero and standardizing the variance to 1. To standardize features, we subtract the mean from each observation and then divide the result by the standard deviation:

The result of the preceding transformation is called the z-score and represents how many standard deviations a given observation deviates from the mean. In this recipe, we will implement standardization with scikit-learn.

How to do it...

To begin, we will import the required packages, load the dataset, and prepare the train and test sets:

1. Import the required Python packages, classes and functions:

import pandas as pd
from sklearn.datasets import load_boston
from sklearn...