jeanne-ado-mlops-dab

This directory contains an ML project based on the default Databricks MLOps Stack, defining a production-grade ML pipeline for automated retraining and batch inference of an ML model on tabular data.

See the Project overview for details on the ML pipeline and code structure in this repo.

Using this repo

The table below links to detailed docs explaining how to use this repo for different use cases.

If you're a data scientist just getting started with this repo for a brand new ML project, we recommend starting with the Project overview and ML quickstart.

When you're satisfied with initial ML experimentation (e.g. validated that a model with reasonable performance can be trained on your dataset) and ready to deploy production training/inference pipelines, ask your ops team to follow the MLOps setup guide to configure CI/CD and deploy production ML pipelines.

After that, follow the ML pull request guide and ML resource config guide to propose, test, and deploy changes to production ML code (e.g. update model parameters) or pipeline resources (e.g. use a larger instance type for model training) via pull request.

Role	Goal	Docs
First-time users of this repo	Understand the ML pipeline and code structure in this repo	Project overview
Data Scientist	Get started writing ML code for a brand new project	ML quickstart.
Data Scientist	Update production ML code (e.g. model training logic) for an existing project	ML pull request guide
Data Scientist	Modify production model ML resources, e.g. model training or inference jobs	ML resource config guide
MLOps / DevOps	Set up CI/CD for the current ML project	MLOps setup guide

Monorepo

It's possible to use the repo as a monorepo that contains multiple projects. All projects share the same workspaces and service principals.

For example, assuming there's existing repo with root directory name monorepo_root_dir and project name project1

1. Create another project from cookiecutter with project name project2 and root directory name project2.

2. Copy the internal directory project2/project2 to root directory of existing repo monorepo_root_dir/project2.

3. Copy yaml files from project2/.azure/devops-pipelines/ to monorepo_root_dir/.azure/devops-pipelines/ and make sure there's no name conflicts.