Linear Regression is commonly used in statistical modelling to characterise the relationship between input variables(x) and output variables(y). This is commonly used in Machine Learning(ML) to create a linear model which will allow us to predict the values of a data-set.

**The aim of this article is to :**

- explain the basics of simple linear regression in ML
- use least squared error(LSE) as a measure of model quality
- make you familiar with ML jargon
- find the mathematical model of values using python, by implementing LSE and simple linear regression

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