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Solid tutorial on using Ibis for feature engineering that stays in-database instead of pulling everything into memory. The Pandas-like API with DuckDB execution is a nice combo for ML practitioners working with larger datasets who want portability without rewriting SQL everywhere.

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How to Build Portable, In-Database Feature Engineering Pipelines with Ibis Using Lazy Python APIs and DuckDB Execution

In this tutorial, we demonstrate how we use Ibis to build a portable, in-database feature engineering pipeline that looks and feels like Pandas but executes entirely inside the database. We show how we connect to DuckDB, register data safely inside the backend, and define complex transformations using window functions and aggregations without ever pulling raw […] The post How to Build Portable, In-Database Feature Engineering Pipelines with Ibis Using Lazy Python APIs and DuckDB Execution

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