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Merge pull request #108364 from rmca14/fix-issues
Resolve build issues PM publish
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articles/machine-learning/how-to-manage-environments-v2.md

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The following example is a YAML specification file for an environment defined from a conda specification. Here the relative path to the conda file from the Azure Machine Learning environment YAML file is specified via the `conda_file` property. You can alternatively define the conda specification inline using the `conda_file` property, rather than defining it in a separate file.
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:::code language="yaml" source="~/azureml-examples-main/cli/assets/environment/docker-image-plus-conda.yml":::
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:::code language="yaml" source="~/azureml-examples-main/cli/assets/environment/docker-image-plus-conda.yaml":::
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To create the environment:
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articles/machine-learning/how-to-use-mlflow-cli-runs.md

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1. Create a `conda.yml` file with the dependencies you need:
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:::code language="yaml" source="~/azureml-examples-main//sdk/python/using-mlflow/deploy/environment/conda.yml" highlight="7-8" range="1-12":::
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:::code language="yaml" source="~/azureml-examples-main//sdk/python/using-mlflow/deploy/environment/conda.yaml" highlight="7-8" range="1-12":::
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1. Reference the environment in the job you're using.
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articles/machine-learning/reference-yaml-environment.md

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## YAML: Docker image plus conda file
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:::code language="yaml" source="~/azureml-examples-main/cli/assets/environment/docker-image-plus-conda.yml":::
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:::code language="yaml" source="~/azureml-examples-main/cli/assets/environment/docker-image-plus-conda.yaml":::
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## Next steps
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