Both Normalization and Standardization are used for **Feature Scaling**. Below are the differences between them.

## Standardization |
## Normalization |

Data should follow a Normal Distribution. | It is not required for data to follow a Normal Distribution. |

The value lies from -x and +x. There is no boundary range. The mean and standard deviation of standardized data is 0 and 1 respectively. |
The value lies between 0 and 1 or -1 and +1. |

Data can be standardized using methods like z-score. |
Data can be normalized using methods like MinMax Scaler. |

Mean and Standard Deviation are used for Scaling. |
Minimum and Maximum values are used for Normalization. |

Standardization is slightly affected by outliers. | Normalization is slightly highly affected by outliers. |

## Z – Score Formula

A z-score tells you where the value lies on a normal distribution curve.

z-score =

where

Î¼ = mean

Ïƒ = standard deviation

x = current value

## MinMaxScaler Formula

MinMaxScaler is a normalization method that uses the maximum and minimum values of a distribution to calculate the normalized value.

where

x = current value

xmin = minimum value of the distribution

xmax = maximum value of the distribution