Edit ‘the_seventy_maxims_of_maximally_effective_machine_learning_engineers’

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osmarks 2025-03-02 11:05:39 +00:00 committed by wikimind
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@ -3,7 +3,7 @@ Based on [[https://schlockmercenary.fandom.com/wiki/The_Seventy_Maxims_of_Maxima
*. Preprocess, then train. *. Preprocess, then train.
*. A training loop in motion outranks a perfect architecture that isnt implemented. *. A training loop in motion outranks a perfect architecture that isnt implemented.
*. A debugger with a stack trace outranks everyone else. *. A debugger with a stack trace outranks everyone else.
*. Regularization covers a multitude of overfitting sins. *. Regularization covers a multitude of sins.
*. Feature importance and data leakage should be easier to tell apart. *. Feature importance and data leakage should be easier to tell apart.
*. If increasing model complexity wasnt your last resort, you failed to add enough layers. *. If increasing model complexity wasnt your last resort, you failed to add enough layers.
*. If the accuracy is high enough, stakeholders will stop complaining about the compute costs. *. If the accuracy is high enough, stakeholders will stop complaining about the compute costs.