John Mount shares an extract from Mount and Nina Zumel’s Practical Data Science with R, 2nd Edition:
This section reflects an important design decision in the book: teach model evaluation first, and as a step separate from model construction.
It is funny, but it takes some effort to teach in this way. New data scientists want to dive into the details of model construction first, and statisticians are used to getting model diagnostics as a side-effect of model fitting. However, to compare different modeling approaches one really needs good model evaluation that is independent of the model construction techniques.
Click through for that extract. I liked the first edition of the book, so I’m looking forward to the 2nd.