Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
MIT License
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The repository now contains the following patterns that have been implemented:
1. Classical / Tabular Machine Learning Model
a. Supports Azure DevOps and GitHub Actions including the deployment of Infrastructure with both the platforms.
b. Supports Azure Data Explorer based Monitoring, Data Drift and Anomaly Detection. It is enabled for Terraform and can be invoked via Python SDKv1 or Azure ML CLI v2 (aml-cli-v2).
c. Can deploy both online as well as batch end points.
d. Supports MLOPs pipelines with Azure ML (AML) CLI v2, Python SDK V1 and V2.
e. Contains Responsible AI and python test modules.
f. Support for Feathr Feature store.
2. Computer Vision (CV) Model
a. Supports Azure DevOps and GitHub Actions. Note that GitHub Actions are only working for Azure ML CLI v2 (aml-cli-v2).
b. Supports MLOPs pipelines with Azure ML (AML) CLI v2, and Python SDK V1.
c. Can deploy both online as well as batch end points.
3. Natural Language Processing (NLP) Model
a. Supports for Azure DevOps and GitHub Actions. Note that GitHub Actions are only working for Azure ML CLI v2 (aml-cli-v2).
b. Supports MLOPs pipelines with Azure ML (AML) CLI v2, and Python SDK V2.
c. Can deploy both online as well as batch end points.
Other Patterns included in the release:
Full Changelog: https://github.com/Azure/mlops-templates/commits/v1.1.0