Data Normalization vs. Standardization – Explained

Learn about normalization and standardization techniques to scale your data correctly, ensuring better model performance. These methods adjust data ranges, making comparisons easier and improving the accuracy and convergence of machine learning algorithms.

Did you know that properly preparing your data can improve your model’s performance?

Techniques like normalization and standardization help scale data correctly, leading to better results and easier interpretation.

Want to know the difference between these two techniques? Keep reading we’ll explain it in a simple way! But first, let’s quickly understand why data preprocessing is important in machine learning.

Data preprocessing in Machine Learning

In Machine Learning, you can describe Data preprocessing as the process of preparing raw data for ML algorithms. It requires data preprocessing steps such as Data cleaning (Fixing incorrect or incomplete data), Data reduction (Removing redundant or irrelevant data), and Data transformation (Converting data to a preferred format).

This ...