> I also think you miss the point of academic papers. The goal is not to build a product, but rather to understand algorithms.
I actually don't, being a researcher myself (not in ML, but in a field that uses a lot of it). I'm just saying that real-world datasets in the industry are nothing like the toy datasets that a lot of papers from universities are written with... there's a lot more noise, and you'd never be able to get a good classification (for example) using just one coherent set of techniques.
On the other hand, KDD/WWW/ICML and other data mining conferences are increasingly dominated by industry folks now, so my experience may not be as common anymore.
I actually don't, being a researcher myself (not in ML, but in a field that uses a lot of it). I'm just saying that real-world datasets in the industry are nothing like the toy datasets that a lot of papers from universities are written with... there's a lot more noise, and you'd never be able to get a good classification (for example) using just one coherent set of techniques.
On the other hand, KDD/WWW/ICML and other data mining conferences are increasingly dominated by industry folks now, so my experience may not be as common anymore.