What is feature scaling, and why is it important for machine learning? Which algorithms require scaled features, and which do not?

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Feature scaling is the process of transforming numerical features to a common scale without distorting differences in their ranges. It ensures that all features contribute proportionally to the model rather than having some features dominate due to their larger magnitude.