Developing a linear regression model

After understanding the concepts of regression analysis, multicollinearity, and dummy variables, it's time to get some hands-on experience with regression analysis. Let's learn how to build the regression model using the scientific toolkit for machine learning (scikit-learn):

1. We will first load the dataset using the read_csv() function:

# Import pandas
import pandas as pd

# Read the dataset using read_csv method
df = pd.read_csv("Advertising.csv")

# See the top-5 records in the data
df.head()

This results in the following output:

Now that we have loaded the Advertising.csv dataset using read_csv() and checked the initial records using the head() function, we will split the data into two parts: dependent or target variable and independent variables or features.

2. In this step, we will split the data two times:

• Split into two parts: dependent or target variable and independent variables or features.
• Split data into training and...