Code repository for this post is here: you can see the MLFlow Recipes template in the main branch and the filled-in template on the fill-in-steps branch. The announcement of MLFlow 2.0 included a new framework called MLFlow Recipes. For a Data Scientists, using MLFlow Recipes means cloning a git repository, or "template", that comes with a ready-to-go folder structure for any regression or binary classification problem. This folder structure includes everything, from library requirements, configuration, notebooks and tests, that's needed to make a data science project reproducible and production-ready. It's easy to start a new project with MLFlow Recipes -- git clone a template from the MLFlow repository, and you are good to go.