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# ask-anything
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Compare to a baseline. I often find it's good to deploy early because I often learn a lot when the model is in production. Also the biggest win for me is fixing mislabeled data. And for some projects, I do need some creative feature engineering to solve it. Rarely do my projects fail succeed because of good HPO. It matters, I just find it matters less than other things and it's not worth the extra training time until the very end
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Also... Best is sometimes hard to define. That's why it's helpful to deploy early because the end user doesn't care about f1 scores and you can have better precision / recall conversations when you have a real model running in production
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