Notes on data engineering, AI and building things end to end.
DuckDB skips the infrastructure bill a cloud warehouse demands — but it’s not a universal replacement. Here’s when dbt + DuckDB genuinely wins, and where it stops making sense, with real project examples.
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Accuracy lies on imbalanced datasets. Here’s what to measure instead, which techniques actually help, and how to pick the right precision/recall tradeoff — with real examples.
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Most data science and data engineering portfolios fail on the same five mistakes — misleading accuracy metrics, untested pipelines, black-box models, and unverifiable results. Here’s what to check instead, with real examples.
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A notebook that prints an accuracy score is a script. Here’s what actually separates it from a data product — serving layers, version tracking, usable interfaces, and visible reasoning — with real examples.
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