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    <description>Train an ML model on your CSV — sklearn and other ML packages running entirely in your browser via Pyodide + WebAssembly. No server, no uploads.</description>
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      <title>Adversarial Validation</title>
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      <pubDate>Thu, 23 Apr 2026 00:00:00 GMT</pubDate>
      <description>A ten-line trick for finding data leaks and distribution shift: train a classifier to predict whether a row came from train or test, then read off which features it leans on.</description>
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      <title>Feature Importance and Partial Dependence Plots</title>
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      <pubDate>Sat, 18 Apr 2026 00:00:00 GMT</pubDate>
      <description>Cracking open the black box: which inputs is your model actually using, and how does each one bend the prediction. Interactive widget, scribble diagrams, no Python.</description>
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      <title>Weighted Ensemble L2</title>
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      <pubDate>Sat, 18 Apr 2026 00:00:00 GMT</pubDate>
      <description>What AutoGluon's WeightedEnsemble_L2 actually does: Caruana's 2004 greedy ensemble selection with replacement. Not L2 regularization — layer 2. Not sklearn — pure NumPy.</description>
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