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ML engineering pipelines

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

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How to do feature selection with VarianceThreshold in Python

This code demonstrates how to use scikit-learn's VarianceThreshold to remove low-variance features from a NumPy array, keeping only those that vary enough to be useful for modeling.

feature selection sklearn machine learning
Python 
import numpy as np
from sklearn.feature_selection import VarianceThreshold

def main():
    # Mock dataset: 4 samples, 5 features
    X = np.array([
        [0.1, 0.2, 1.0, 1.0, 0.5],
        [0.2, 0.2, 0.0, 1.0, 0.4],
        [0.1, 0.2, 1.0, 1.0, 0.6],
        [0.3, 0.2, 1.0, 0.0, 0.5]
    ])

    # Select features w…
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