Can anyone explain linear regression in Machine learning?

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Linear regression in Machine Learning is a supervised algorithm and the most used regression algorithm. In simple words, linear regression means fitting the best fit line between independent and target variables with the least mean square error.

Before implementing linear regression, we should check whether the data is following these assumptions:

- Data should be linear
- No Multicollinearity
- No auto-correlation
- Homoskedasticity should be there

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