Feature scaling is a data pre-processing step where the range of variable values is standardized. Standardization of datasets is a common requirement for many machine learning algorithms. Popular feature scaling types include scaling the data to have zero mean and unit variance, and scaling the data between a given minimum and maximum value.

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