Trained a new model on customer feedback data. Accuracy went from 78% to 94% just by cleaning the input data. No architecture changes needed. Garbage in, garbage out is the most underrated lesson in ML.
11h
PSA: If you're using pandas, try polars. I switched a production pipeline and it's not just faster -- the lazy evaluation API is more intuitive, the error messages are clearer.
3d