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Samples for use with MLOps

MLOpsSamples 최신버젼 다운로드

최종 버전 다운로드 (.zip)

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# Run your notebooks as-is on AzureML Service with MLOps extensions

We use MLOps to manually or automatically trigger builds due to Github PRs and changes.  The control plane is in DevOps and AzureML Service provides numerous capabilities to track your assets when running Jupyter notebooks local or in the cloud.

## AzureML improves your MLOps experience!

### Build Definitions

[Run Recommender Notebooks](https://dev.azure.com/emcmanu/NotebookPipelineDemo/_build?definitionId=15)

[Validate Notebook Changes](https://dev.azure.com/emcmanu/NotebookPipelineDemo/_apps/hub/ms.vss-ciworkflow.build-ci-hub?_a=edit-build-definition&id=14)

This folder demonstrates how to build, train and test notebooks from our [Recommendation Project](http://github.com/Microsoft/Recommenders) project so you can make your own Recommendation system.

# Contributing

This project welcomes contributions and suggestions.  Most contributions require you to agree to a
Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us
the rights to use your contribution. For details, visit https://cla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide
a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions
provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).
For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or
contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.

MLOpsSamples

MLOpsSamples 최신버젼 다운로드

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