Instruction: Discuss the benefits of feature scaling and its impact on different machine learning algorithms.
Context: This question evaluates the candidate's understanding of feature scaling techniques like normalization and standardization, and their importance in optimizing model training and performance.
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The way I'd explain it in an interview is this: The purpose of feature scaling is to make features comparable enough that models sensitive to magnitude do not let one large-scale variable dominate just because of its units. That is especially important for distance-based models, gradient-based optimization,...