This session - statistics! No wait, don't run!
One of the bits of feedback we get here at Qld AI is people saying, "I get the idea behind [some ML concept], but I can't figure out how to code the maths, how do I learn?". Alternatively, people can understand the statistical underpinnings of ML when put into code, but not as equations on paper. This doesn't just happen in Qld AI, it's actually a pretty big problem in ML education generally. It's big enough that a book has just been written where both approaches are taught side-by-side.
Some of you who have been around a while may know (or been taught by!) Dr Yoni Nazarathy, a guy passionate about making this sort of knowledge accessible. Well, he's just co-authored "Statistics with Julia" , wherein he uses Julia (a purpose-built data science language) to connect statistical theory to the applied world of machine learning and data science. He's going to make explicit both how a lot of the complex concepts can be reduced to simple code, and how a knowledge of the concepts can be used to build more sophisticated models. So if you're looking to learn how to be a better software engineer with statistical shortcuts, add more tools to your analysis toolkit or simply learn how Julia works, come along.
Link to the book PDF: https://people.smp.uq.edu.au/YoniNazarathy/julia-stats/StatisticsWithJulia.pdf
**AS A REMINDER. River City Labs, not Thoughtworks. In case you get lost, it's level 3, upstairs from where the main QLD AI event is held.**