Reference library

ML engineering pipelines

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

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ML engineering pipelines easy

Compare Model A vs Model B Metrics in Python

A script that simulates and compares metrics between two ML models, showing a formatted diff table for quick insight.

model comparison mock metrics
Python 
import random


def compare_a_b(samples=5):
    """Mock comparison of model A vs model B predictions."""
    metrics = ["accuracy", "precision", "recall", "f1"]
    print(f"{'Metric':<12}{'Model A':>10}{'Model B':>10}{'Diff':>10}")
    print("-" * 42)

    random.seed(42)
    for metric in metrics:
        a = round(r…
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ML engineering pipelines — Python code examples

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