Building a Simple Linear Regression Model with Sci-kit Learn

Building a Simple Linear Regression Model with Sci-kit Learn

We will learn how to build a Simple Linear Regression Model using Sci-kit Learn. Simple Linear Regression is a regression algorithm that shows the relationship between a single independent variable and a dependent variable. The Sci-kit Learn library contains a lot of tools used for machine learning.

In this guide, we will learn how to build a Simple Linear Regression Model using Sci-kit Learn. Simple Linear Regression is a regression algorithm that shows the relationship between a single independent variable and a dependent variable.

The Sci-kit Learn library contains a lot of tools used for machine learning. We will build a model to predict sales revenue from the advertising dataset using simple linear regression.

Prerequisite

  • A PC with Jupyter Notebook IDE
  • Advertising dataset from Kaggle

The formula of simple linear regression is:

            y = θ0x + θ1

PythonCopy

θ0 represents the slope of the regression line

θ1 represents the intercept of the regression line

x is the independent variable

y is the dependent variable

IMPORTING DATASET

Let’s import our libraries

## importing libraries
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
%matplotlib inline

## importing dataset
advert = pd.read_csv('Advertising.csv')
## view first 5 entries
advert.head()

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