The Steps that we are going to follow to complete this implementation is as follows:
Importing the important libraries which are numpy, pandas, sklearn, matplotlib.
Reading the data-set from the CSV file.
Splitting the data-set into independent (x) and dependent (y) variables.
Dividing the complete data-set into training and testing data-set.
Implement our classifier based on simple linear regression.
This is how you load the CSV file from your desktop to the Google colab. The CSV file can be found here.
Step 1: Importing the necessary libraries.
Step 2. Reading the data-set from the CSV file.
Step 3: Splitting the data-set into independent (x) and dependent (y) variables.
Step 4: Dividing the complete data-set into training and testing data-set
Step 5: Implement our classifier based on simple linear regression.
Source: Linear Regression
Thank you Guys for spending your time reading my Blog, stay tuned for more updates. Let me know what is your opinion about this tutorial in the comment section below. Also if you have any doubts regarding the code, comment section is all yours. Have a nice day. The entire source code for this tutorial can be found in the GitHub.