PADL is the next ML-ops tool you should learn

You've spent a few days with sweat and tears putting together a PyTorch model in a Jupyter notebook, tinkering with parameters, trying various preprocessing methods, post-processing methods, validating the model results on examples, and checking on validation data sets that the model performs well. The results are good, you're happy, your boss (if you have one) and colleagues are happy. Now you'd like to share the results, so that other people can play with the model; so what do you do? None of these are ideal. It doesn't have to be this way… In this blog post we discuss how to use PADL around an NLP code example.