How Linear Regression works ?

Linear regression aims to model the relationship between two variables by fitting a linear line.

It is assumed that dependent variable can be predicted by independent variable by fitting a best fit line, when there is one independent variable involved the phenomenon is known as simple linear regression while when multiple independent variables are involved then phenomenon is known multiple linear regression.

Linear regression is a supervised learning algorithm

How linear regression works ?

The regression line (yellow color) is the best fit line for the model and red points are coordinates of data

Equation of linear regression line

y = mx + c

y = Dependent variable (labels to data)

x = Independent variable (input data)

m = Slope of line (coefficient of x)

c = Intercept