I had an incredible time organizing and speaking at the AI/machine learning track at QCon London 2020 where I invited and shared the stage with incredible speakers Vincent Warmerdam, Susanne Groothuis, Peter Elger, and Hien Luu.

QCon is a global software conference for software engineers, architects, and team leaders, with over 1,600 attendees in London. All speakers have a software background.

In my talk, I distilled ten central concepts in applied machine learning that should help software engineers break into the field.

I learned quite a bunch from the talks and discussions. I agree with Vincent that we have to build business rules into chatbots (especially when considering where the technology is at the moment). Susanne’s approach to having different groups label the same sentiment-analysis dataset, and then comparing group labels was quite interesting. Peter’s advice to experiment with cloud ML service has merit in plenty of circumstances. And Hien’s introduction to MLflow showed clear value in establishing a rigorous ML infrastructure that allows companies to roll out (and track) ML experiments quickly.

I’d like to thank them for sharing their time and insights. The videos should roll out publicly to the infoQ website over the next few weeks (then to YouTube later).