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

Duration : 1 day

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To train a machine learning model with Azure Machine Learning, you need to make data available and configure the necessary compute. After training your model and tracking model metrics with MLflow, you can decide to deploy your model to an online endpoint for real-time predictions.

Throughout this learning path, you explore how to set up your Azure Machine Learning workspace, after which you train and deploy a machine learning model.

Audience

• Beginner
• Data Scientist

Prerequisites

None

Contents

• Make data available in Azure Machine Learning
• Work with compute targets in Azure Machine Learning
• Work with environments in Azure Machine Learning
• Run a training script as a command task in Azure Machine Learning
• Track model training with MLflow in jobs
• Register an MLflow model to Azure Machine Learning
• Deploy a model to a managed online endpoint