How do you keep track of model iterations in a project?

Summary

At a company with immature machine learning processes, chaos arises from testing different modeling approaches that involve numerous iterations. This leads to challenges in tracking model runs and an abundance of scattered Jupyter notebooks. An employee is working on developing an internal tool to address these challenges, focusing on the use of XGBoost.