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As by far the most upvoted solution has by now included unit tests, I will just incorporate that there exists a library which supports unit assessments progress for NN (only in Tensorflow, sadly).

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These bugs may even be the insidious form for which the network will train, but get caught at a sub-best Option, or even useful reference the resulting network doesn't have the specified architecture. (This can be an illustration of the difference between a syntactic and semantic error.)

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These facts sets are very well-examined: In the event your teaching decline goes down right here although not with your primary data set, you could have concerns in the information established.

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attempt diverse optimizers: SGD trains slower, click now but it really leads to a lessen generalization mistake, though Adam trains quicker, though the exam reduction stalls to a better worth

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