Clojure for Data Science  the good, the bad, and the ugly by Simon Belak
Channel: Clojure Days
Date: 2016-04-19

Having programmers do data science is terrible, if only everyone else were not even worse. The problem is of course tools. We seem to have settled on either: a bunch of disparate libraries thrown into a more or less agnostic IDE, or some point-and-click wonder which no matter how glossy, never seems to trully fit our domain once we get down to it. The dual lisp tradition of grow-your-own-language and grow-your-own-editor gives me hope there is a third way.
This presentation is a meditation on how I approach data problems with Clojure, what I believe the process of doing data science (and by extension: running a data-driven company) should look like and the tools needed to get there. Some already exists (or can at least be bodged together); others can be made with relative ease (and we are already working on some of these); while a few will take a lot more hammock time.