I'd say that's more what cost functions are for, but that is neither here nor there. I think the biggest takeaways are... 1) Machine learning in large softwar

I'd say that's more what cost functions are for, but that is neither here nor there. I think the biggest takeaways are... 1) Machine learning in large software projects is complex because decisions made by one algorithm can influence the data of other algorithms, creating massive biasing. 2) Simple cross-validation / hold back methodology is limited as we expand what we want machine learning to be able to handle. Reason: big data is too big and "correctness" is difficult to evaluate for things like Q/A systems.