**Data science Day 8:**

Data transformation is one of the critical steps in Data Mining. Among many data transformation methods, **normalization** is a most frequently used technique. For example, we can use **Z-score normalization** to reduce possible noise in sound frequency.

We will introduce three common normalization method, **Max-Min Normalization, Z-Score Normalization, Scale multiplication**.

**Max-Min Normalization**x_normal= (x- min(x))/ (max(x)- min(x))

*it will scale all the data between 0 and 1.*

Example: Chinese high schools use 150 point scale, USA high schools use 100 point scale and Russian high schools use 5 point scale.

**Z-Score Normalization**X_z-normal= (X- mean)/ sd

*It will transform the data*in*units relative to the standard deviation.*Example: It is useful when comparing data sets with different units (cm and inch).

**Scale multiplication**

Z_z-normal =X*10 or Z_z-normal =X/10

*It will transform the data*in*scales of*muliple*of 10.*

Example: Some money transactions are too large, we will divide 1000 to make it viewer friendly.

**Happy Studying** 🐷!

Source Code