It turns out that it’s shockingly easy to do some very reasonable things with data (aggregate, slice, average, etc.), and come out with answers that have 2000% error! In this post, I want to show why that’s the case using some very simple, intuitive pictures. The resolution comes from having a nice model of the world, in a framework put forward by (among others) Judea Pearl.
Data frames are lists …
Danielle Dean introduces the landscape and challenges of predictive maintenance applications in the manufacturing industry.