Hi there! I decided to almost re-write the model validation section since it didn't reflect real case scenarios.
Hopefully in the two new chapters you will gain a deeper knowledge on methodological aspects on model validation through classical cross-validation, bootstrapping, and going further in the nature of the error. And also take advantage of validation when data is time dependent.
There is a lot more to tell about model validation, but it's a kick start.
Coming soon, there will be an update on methodological aspects in data preparation.
First published at: http://blog.datascienceheroes.com/model-performance-in-data-science-live-book