I am a believer in Linear Algebra and always fascinated with its powerful application. Linear Regression is one of the first applications of Linear Algebra that I’ve learned. Simply put, Linear Regression is a process of generalizing the linear relationship between a scalar variable (dependent~y) and one or more explanatory variables (independent~x) by minimalizing the distance between the data and the regression function. a.k.a. the line of best fit in Simple Linear Regression.