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# <system-managed>
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from azureml.core.runconfig import RunConfiguration
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from azureml.core.conda_dependencies import CondaDependencies
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run_system_managed = RunConfiguration()
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# Specify the conda dependencies with scikit-learn
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run_system_managed.environment.python.conda_dependencies = CondaDependencies.create(conda_packages=['scikit-learn'])
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# </system-managed>
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print(run_system_managed)
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# <user-managed>
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from azureml.core.runconfig import RunConfiguration
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run_user_managed = RunConfiguration()
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run_user_managed.environment.python.user_managed_dependencies = True
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# Choose a specific Python environment by pointing to a Python path. For example:
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# run_config.environment.python.interpreter_path = '/home/ninghai/miniconda3/envs/sdk2/bin/python'
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# </user-managed>
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print(run_user_managed)
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