It is one of the most widely known modeling techniques. Simple linear regression is useful for finding relationships between two continuous variables. One is a predictor or independent variable and the other is a response or dependent variable. It looks for a statistical relationship but not a deterministic relationship.

Linear Regression establishes a relationship between the dependent variable (Y) and one or more independent variables (X) using a best fit straight line (also known as a regression line).

It is represented by an equation Y=a+b*X + e, where a is the intercept, b is the slope of the line and…

Sharat Kedari

Machine Learning Engineer

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