DP-3007 – Train and deploy a machine learning model with Azure Machine Learning

  • Duration: 10 weeks
Categories:

1. Make data available in Azure Machine Learning

Learn about how to connect to data from the Azure Machine Learning workspace. You’re introduced to datastores and data assets.

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2. Work with compute targets in Azure Machine Learning

Learn how to work with compute targets in Azure Machine Learning. Compute targets allow you to run your machine learning workloads. Explore how and when you can use a compute instance or compute cluster.

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3. Work with environments in Azure Machine Learning

Learn how to use environments in Azure Machine Learning to run scripts on any compute target.

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4. Run a training script as a command job in Azure Machine Learning

Learn how to convert your code to a script and run it as a command job in Azure Machine Learning.

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5. Track model training with MLflow in jobs

Learn how to track model training with MLflow in jobs when running scripts.

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6. Register an MLflow model in Azure Machine Learning

Learn how to log and register an MLflow model in Azure Machine Learning.

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7. Deploy a model to a managed online endpoint

Learn how to deploy models to a managed online endpoint for real-time inferencing.

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