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An automated data pipeline and lakehouse architecture for NBA and WNBA statistics, utilizing LLMs for semantic search and predictive insights.
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The project is a personal experiment or portfolio piece with very low engagement (2 stars). It applies standard Retrieval-Augmented Generation (RAG) and data engineering patterns to a specific vertical (basketball stats). While frontier labs won't build a niche NBA lakehouse, the approach is easily reproducible by any developer using existing sports APIs and LLM frameworks.
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