Data Scaling for Beginners

How to scale your data to render it suitable for model building

Image by Unsplash

About the Author

Benjamin O. Tayo is a data science educator, tutor, coach, mentor, and consultant. Contact me for more information about our services and pricing: benjaminobi@gmail.com

Dr. Tayo has written close to 300 articles and tutorials in data science for educating the general public. Support Dr. Tayo’s educational mission using the links below:

PayPal: https://www.paypal.me/BenjaminTayo

CashApp: https://cash.app/$BenjaminTayo

INTRODUCTION

In the machine learning process, data scaling falls under data preprocessing, or feature engineering. Scaling your data before using it for model building can accomplish the following:

• Scaling ensures that features have values in the same range
• Scaling ensures that the features used in model building are dimensionless
• Scaling can be used for detecting outliers

There are several methods for scaling data. The two most important scaling techniques are Normalization and Standardization.

Data Scaling Using Normalization