Vincent Warmerdam

For well over a decade, Python notebooks revolutionized our field. They gave us so much creative freedom and dramatically lowered the entry barrier for newcomers.

This is the story of a fun idea that turned into a huge benchmark before it turned into a rabbit hole. I was trying to figure out reasonable default parameters for some of the components in the skrub library.

In this talk I will try to show you what might happen if you allow yourself the creative freedom to rethink and reinvent common practices once in a while. As it turns out, in order to do that, natural intelligence is all you need.

Let's say you've to some unlabelled data and you want to train a classifier. You need annotations before you can model, but because you're time-bound you must stay pragmatic.

This will be a technical talk where I'll explain the inner workings of the machine learning algorithms inside of Rasa. In particular I'll talk about why the transformer has become a part in many of our algorithms and has replaced RNNs.