Linear regression predicts a real-valued output based on input and is a supervised machine learning algorithm where the predicted output is continuous and has a constant slope. It is a statistical method that is used for predictive analysis. It’s used to predict values within a continuous range, (e.g. share market, sales, salary, product price, etc.).

**There are two categories**

i. Simple regression

ii. Multivariable regression

**Simple regression**

Simple Linear Regression is characterized by one independent variable and It uses the traditional slope-intercept form, where **m** and **b** are the variables our algorithm will try to **learn** to produce the most accurate predictions.

**x** represents our input data and **y** represents our prediction.

**y = mx+b**