How do I implement feature scaling in my machine learning model?

How do I implement feature scaling in my machine learning model?

Feature scaling is essential for many machine learning algorithms. You can implement it using techniques like Min-Max scaling or Standardization.

What is Min-Max scaling and how does it work?

Min-Max scaling transforms features to a fixed range, usually [0, 1]. It subtracts the minimum value and divides by the range.

When should I use Standardization instead?

Standardization is useful when your data follows a Gaussian distribution. It centers the data around zero with a unit variance.

Can you show me an example of how to apply these methods in Python?

Sure! You can use libraries like scikit-learn. For Min-Max scaling, use MinMaxScaler, and for Standardization, use StandardScaler.