Hello @Caiwen Wu ,
As discussed, you can run Code as AML Jobs Instead of Notebooks. To automate scripts as jobs/pipelines (instead of interactive notebooks), please find the below docs:
- AML Jobs Overview: Create and submit jobs: Covers CLI v2 and SDK options for running code as jobs. Microsoft Docs: Submit and track Azure ML jobs
- Convert Notebooks to Jobs: Run notebooks as jobs: Steps to submit a notebook directly as an AML job. Microsoft Docs: Run Jupyter Notebooks as jobs
- AML Pipelines: Design workflows to automate multi-step tasks. Create pipelines for recurring jobs: Microsoft Docs: Create ML pipelines.
- Schedule Jobs: Use AML Pipelines with schedules or Azure Logic Apps. Trigger jobs on a schedule:
Why Use Jobs Instead of Notebooks?
- Jobs are designed for unattended execution (no interactive authentication required).
- Jobs leverage the workspace’s managed identity by default.
- Jobs can run on dedicated compute clusters, which auto-scale and cost less than persistent compute instances.
- Logs and outputs are stored automatically in the AML workspace.
Running Code as Azure Machine Learning (AML) Jobs Instead of Notebooks:
- Submitting Training Jobs: Azure Machine Learning provides multiple methods to submit training jobs, allowing you to run your code as a job rather than within a notebook environment. This approach is beneficial for scaling and automating your machine learning workflows. For detailed instructions on configuring and submitting training jobs, consult the following resource: learn.microsoft.com
- Running a Training Script as a Command Job: To convert your existing code into a script and execute it as a command job in Azure Machine Learning, you can follow the guidelines provided in this module: learn.microsoft.com
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Thank you