A Z-score measures how far a data point is from the mean in terms of standard deviations, providing context that raw numbers lack. This statistical tool helps identify outliers and compare values across different scales, crucial for anomaly detection and feature scaling in machine learning models. Developers should be cautious about applying Z-scores to non-normally distributed data due to potential misinterpretation.
Read the full article at Towards AI - Medium
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