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#experiment-tracking

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01 ·Machine Learning Basics·★ MEMBER·10 min read Data Leakage and Experiment Hygiene — When the Score Is Too Good, Suspect It When a model scores better than you expected, that is not good news yet. This article splits data leakage into five concrete shapes — outcome-derived columns, preprocessing before the split, time running backwards, duplicates and groups, and a worn-out test set — then covers the detection moves that actually find them and the experiment records that let you dissect the day the number jumped.