Python Linear Regression Tutorial

Introduction

Today we are going to fit a linear model between two variables x and y using python libraries. Linear regression is used to find a linear relationship between target variable and another variable used for prediction. If you are not familiar with python don’t loose hope, just look through our python tutorial it will provide for you a good reference point

In this tutorial we use Jupiter note book run on an Anaconda platform and a csv data set with X and Y values .

Step 1: We Import numpy, matplotlib, pandas and seaborn libraries as shown below

Step 2: Using Pandas we read and open our csv data 

Step 3:  Using seaborn, we plot a scatter of y against x to see the behavior of our data values

Step 4: We  then plot a linear regression line using seaborn

Step 5: Further we import and define our regression mode

Step 6: We divide our two data( x and y) into model training and testing data

Step 7: Finally, we Fit the train data to the linear model, predict y values and evaluate the score of the training and prediction model.

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