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Why does using the scikit-learn library's MLPRegressor result in such a boost in training time when compared to constructing the network from scratch? I tried both methods and I found that writing the code from scratch yielded an average training time of ~10 seconds while Sci-Kit Learn trained almost instantly?

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    $\begingroup$ My suspicion would be that Scikit-Learn utilises a lot of numpy, which in turn utilises C (I could be wrong about that!) - a high-performant low-level language. $\endgroup$
    – bradS
    Mar 14 '19 at 16:58
  • $\begingroup$ If I was to code an ANN from scratch in C then do you think it would perform about the same as Scikit-learn (Not that I'll actually do that!) $\endgroup$ Mar 14 '19 at 17:27
  • $\begingroup$ If you are intelligent enough and know how to optimize your code like hell, then Yes, Just check their Source code simple to see :) $\endgroup$
    – Aditya
    Mar 15 '19 at 4:46
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Scikit-learn use numpy and cython to speed-up code.

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