I'm wondering if there are any well-justified end-to-end methodologies for developing machine learning models (classification or regression). At work, there is a guy who developed a methodology for classification and I'm wondering if there is some paper or "common methodology" when developing a machine learning model.
When I go to google, I can find stuff like "how to treat outliers", or how-to-do certain steps when building a model. But I can't find an end-to-end approach. Is there any paper where I could look for?