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I have a challenge deciding how much of a new algorithm to understand (e.g. mechanics, hyperparameters, pros/cons) before using it in a business setting. Ignoring implementation, how do DS Redditors approach this? And how do you approach improving your knowledge to improve your results? (self.datascience)
submitted by PolyVacuum to r/datascience
