I enjoyed giving my “Intro to Amazon Machine Learning” talk at the AWS Denver Boulder meetup. (Shout out to an old friend and colleague who came out to see it.) I didn’t get through the whole pipeline demonstration (I didn’t get a chance to do the batch prediction), but the demo gods were kind and the demo went well.
We also had a good discussion. A few folks present had used machine learning before, so we talked about where AML made sense (hint, it’s not a fit for every problem). Also had some good questions about AML, about performance and pricing. One of the members shared a reinvent anecdote: the AML team looked at all the machine learning used in Amazon and graphed the use cases and solved for the most common ones.
As, usual, I also learned something. OpenRefine is a tool to help you prepare data for machine learning. And when you change the score cut-off, you need to restart your real-time end point.
The “Intro to Amazon Machine Learning” slides are up on SlideShare, and big thanks to the Meetup organizers.