Sunday data/statistics link roundup (4/8)

This is a great article about the illusion of progress in machine learning. In part, I think it explains why the Leekasso¬†(just using the top 10) isn’t a totally silly idea. I also love how he talks about sources of uncertainty in real prediction problems that aren’t part of the classical models when developing prediction algorithms. I think that this is a hugely underrated component of building an accurate classifier - just finding the quirks particular to a type of data.