muser
Re:Surviving Data Science at the Speed of Hype
on Saturday January 31, 2015 @02:18AM (#8976135)
There's lots written in the credit scoring space that I think other industries could look at - especially when it comes to calibration of models. It doesn't matter if the prediction is weak just as long as it is consistent over time periods. Banks rely on this consistency to ensure they are provisioning properly for losses.
Re:2015 Gates Annual Letter
on Thursday January 22, 2015 @11:24AM (#8929971)
It can be a AU$24 flat fee plus potentially any conversion fees for an intl transfer.
Re:Facebook open-sources deep-learning modules
on Friday January 16, 2015 @06:19PM (#8902435)
Could you provide some steps how you could bring everyone one board? We are still having python/R migration issues.
Re:Going Beyond “Make Something People Want”
on Friday January 16, 2015 @02:28AM (#8897628)
16 months old? How did the testing and overlay with PG's 18 startup mistakes go?
Re:The Perilous World of Machine Learning for Fun and Profit
on Tuesday January 06, 2015 @02:52PM (#8846512)
I'm curious about the real world implementation risk and if anyone has a methodology to proactively deal with external factors affecting the model performance. Such as if a feature is highly predictive of a certain outcome is there a framework to measure the volatility based on information outside of the dataset ie. product changes, marketing campaigns etc.