L1 and L2 are two loss functions in machine learning which are used to minimize the error.

**L1 Loss function stands for Least Absolute Deviations.** Also known as LAD.
$L1LossFunction = \sum_{i=1}^n |y_{true}-y_{predicted}|$

**L2 Loss function stands for Least Square Errors.** Also known as LS.
$L2LossFunction = \sum_{i=1}^n (y_{true}-y_{predicted})^2$