MLR is a generalized form of simple linear regression. It is a statistical method used to predict the continuous target variable based on multiple features or explanatory variables. The main objective of MLR is to estimate the linear relationship between the multiple features and the target variable. MLR has a wide variety of applications in real-life scenarios. The MLR model can be represented as a mathematical equation:
Here, 
are the independent variables and 
is a dependent variable. 
intercepts are coefficients of x and 
(the Greek letter pronounced as epsilon) is an error term that will act as a random variable.
Now that we know what linear regression is, let's move on to multicollinearity.
