<p>I've seen a few questions like this lately:</p>

<p><a href="https://stats.stackexchange.com/questions/309037/backpropagation-in-multi-layer-perceptron-mlp-doesnt-converge">Backpropagation in multi-layer perceptron (MLP) doesn&#39;t converge</a></p>

<p>They don't seem programming questions to me: the code is syntactically correct, because it runs, but the result is not the desired one (semantic error). In this case the loss function doesn't decay with epochs or something like that...the OP wasn't completely clear.</p>

<p>Now, do we consider this to be a programming question or not? In my experience, a Neural Network may not converge either because of a bug in the code (off-topic!) or because of issues in the data set, in the weight initialization, hyperparameters setup, wrong regularization approach, etc. (I would say all this is on-topic). However, it's hard in advance to say what is what. In this case, if I had to guess I would say "programming error" because it seems the OP is trying to reproduce a simple case from a book. Anyway, do we consider the question on-topic or not?</p>
