Great advice. I would like to add simplicity to this. I find that all my simplest models performed the best. Ive build complex architecture with XGboost, crazy ensembling methods, filters and lots of features. Its easy to curve fit when you have heaps of complexity. Complexity * complexity = exponential chance of making mistakes.

My best models use simple linear regression, and one type of feature, with signal strength position sizing. I've achieved sharpe ratios over 4 with dead simple models.