No long agendas, no boring announcements – just food, music, a speaker and their ideas.
You're guaranteed to learn something interesting whatever your background.
The perception of data science is like this: You have some nice, tidy data, you use the latest, coolest algorithm, and you get some super clever results. You know it’s good ‘cause your r-squared value is through the roof, and you could play checkers on your confusion matrix.
But the reality is different. That nice, tidy dataset has to be wrangled out of a big, nasty production system. Those cool results have to somehow be translated into a user interface. And in front of that production system, entering that data, clicking on that user interface, is a data scientist’s worst nightmare: People.
As much as we might want to believe that data science is a pure “hard” science, about writing greek letters on chalkboards and stroking our chins, the truth is that what we do is more usefully thought of as a social science. Data science is a lens for understanding human behaviour. It is a tool for communicating with people. This talk is about how my background in Social Anthropology gave me a different approach to doing data science. Data science problems, I believe, are mostly about how to understand humans. Data is a soft science.