Reference library

ML engineering pipelines

Feature prep, batch inference, model-serving hooks, and production ML workflow glue.

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Detect Concept Drift in Python with a Simple Statistical Test

Detect concept drift by comparing the mean of recent data against a reference distribution using a z-score-like threshold.

concept drift statistics ml monitoring
Python 
import random
import statistics

def detect_drift(recent, reference, threshold=1.5):
    ref_mean = statistics.mean(reference)
    ref_std = statistics.stdev(reference)
    
    recent_mean = statistics.mean(recent)
    drift_score = abs(recent_mean - ref_mean) / (ref_std if ref_std > 0 else 1)
    
    drifted = drif…
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