So you’ve spent weeks building a dataset and coding up a neural network. You’ve trained the model, and are getting less-than-stellar results. What do you do next? Deep learning is often seen as a black box, and I’m not going to argue with this view — what sense can you make of tens of thousands of learned parameters? But the …