Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you''ve ever built a predictive model, worked on a ...

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Data quality is critical for successful data processing, with robust statistics essential for handling outliers and ensuring accurate representation. The standard deviation is sensitive to outliers, ...

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When performing the normalization step in data_utils.py, why is the standard deviation of y-values used for the division instead of computing an independent standard deviation for x and y values (as ...