Collection of scripts to implement MLOps using Azure Machine Learning.
Trunk Based Development - linting and unit tests (source:https://learn.microsoft.com/en-us/training/modules/work-linting-unit-test-github-actions/)
- The production code is hosted in the main branch.
- A data scientist creates a feature branch for model development.
- The data scientist creates a pull request to propose to push changes to the main branch.
- When a pull request is created, a GitHub Actions workflow is triggered to verify the code.
- When the code passes linting and unit testing, the lead data scientist needs to approve the proposed changes.
- After the lead data scientist approves the changes, the pull request is merged, and the main branch is updated accordingly.