Last year I nerded out on model accuracy and it was great fun. I would love to do this more at work but unless I fall into it in an existing role I usually am not considered for data science roles because I don't have 7 Ph.Ds. Simple accuracy, R2 for classification, ROC curves, calibration, Brier Skill scores. Good times.

The best book I found at the time was Kuhn & Johnson. If anyone can recommend a better book I'd love to hear it? (Examples in R or Python, it doesn't matter.)