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Why evaluating a machine learning model on the same data it learned from can give misleadingly high accuracy.
A walk through a content-based recommender: from cleaning metadata to ranking similar titles with cosine similarity.
Four habits that keep batch pipelines trustworthy: idempotency, schema checks, observability, and small recoverable steps.