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Comment on Mistakes Programmers Make when Starting in Machine Learningparent

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One nasty aspect of the advice "Don't reinvent solutions to common problems" is it doesn't really provide a way to tell when your problem is really, truly a common problem, which can be a lot more subtle than you might think.

Sometimes the simplest single requirement change - say, works in low memory environment, or handles high latency, or utilizes a GPU, or has a good public API, or has low battery usage, or can save its entire state to disk, or is skinnable, or supports other random feature X - can instantly take all common solutions to a problem and invalidate them. But just as often, it doesn't. Or, just as often, you have to just give up on those requirements for pragmatic reasons.

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