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Made a simple little LLM for generating dbt model config boilerplate using @simonw's all too excellent `llm` tool, see the gist for the prompt + shell script. gist.github.com/PedramNavid/c5…
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5 quality of life changes I’d recommend for tabular problems: • Change your baseline model to LightGBM • Store your data in parquets • Default to leave-one-out feature importance • Use Polars for feature engineering • If you have a GPU, use RAPIDS Nice and quick wins.
@marktenenholtz How good is Polars feature engineering integration with sklearn pipelines and transformers?
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