In this tutorial, we build a production-grade tabular machine learning pipeline using AutoGluon, taking a real-world mixed-type dataset from raw ingestion through to deployment-ready artifacts. We train high-quality stacked and bagged ensembles, evaluate performance with robust metrics, perform subgroup and feature-level analysis, and then optimize the model for real-time inference using refit-full and distillation. Throughout
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