What do you think about the mechanics of machine learning book by Jeremy Howard? It seems to have a systematic approach to fit models and improve them.
At risk of being excessively cheeky, I think you should throw it into xgboost and not worry about it.
I love Jeremy Howard, but if you're doing applied ML on tabular data, tweaking specifics of model construction probably won't get you anything beyond stock xgboost. The concerns highlighted by your sibling commenter jamesblonde end up eating most of your time in deployed ML products, not model construction.
If you're looking to learn about ML model construction I'm sure it's a great book.
I love Jeremy Howard, but if you're doing applied ML on tabular data, tweaking specifics of model construction probably won't get you anything beyond stock xgboost. The concerns highlighted by your sibling commenter jamesblonde end up eating most of your time in deployed ML products, not model construction.
If you're looking to learn about ML model construction I'm sure it's a great book.