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Feature Scalling

Feature scaling is the process of normalizing the range of features in a dataset.

Real-world datasets often contain features that are varying in degrees of magnitude, range, and units.

Therefore, in order for machine learning models to interpret these features on the same scale, we need to perform feature scaling.