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  1. Tutorial: Deploy and query a custom model | Databricks on AWS

    Apr 30, 2025 · Learn the overview and basic steps for performing model serving on Databricks.

  2. Tutorial: End-to-end deep learning models on Azure Databricks

    May 9, 2025 · This tutorial notebook presents an end-to-end example of training a deep learning model in Azure Databricks, including loading data, visualizing the data, setting up a parallel hyperparameter …

  3. MLflow 3 for GenAI - Azure Databricks | Microsoft Learn

    Nov 26, 2025 · Managed MLflow on Databricks extends open source MLflow with capabilities designed for production GenAI applications, including enterprise-ready governance, fully managed hosting, …

  4. Azure Machine Learning MLflow Integration — Consume AML Trained …

    Apr 8, 2022 · I recently was asked questions around consuming an ML Model trained in Azure Machine Learning (AML) from Azure Databricks and made some…

  5. MLflow API reference - Azure Databricks | Microsoft Learn

    Mar 1, 2024 · The open-source MLflow REST API allows you to create, list, and get experiments and runs, and allows you to log parameters, metrics, and artifacts. The Databricks Runtime for Machine …

  6. Workspace Model Registry example - Azure Databricks | Microsoft Learn

    Learn how to use the Workspace MLflow Model Registry to build a machine learning application that forecasts the daily power output of a wind farm.

  7. Azure Databricks MLOps using MLflow - Code Samples | Microsoft …

    Mar 21, 2025 · Get Azure Data Lake Storage Gen2 account name created in step 1 Get Shared Key for Azure Data Lake Storage Gen2 account Execute make databricks-secrets-put to put secret in …

  8. Monitor GenAI in production - Azure Databricks | Microsoft Learn

    Nov 25, 2025 · Learn how to set up automated quality monitoring for your GenAI applications in MLflow by scheduling scorers to run on production traces, enabling continuous assessment of application …

  9. Manage model lifecycle using the Workspace Model Registry (legacy)

    Jun 12, 2025 · The Workspace Model Registry is a Databricks-provided, hosted version of the MLflow Model Registry. The Workspace Model Registry continues to be supported in MLflow 3 as in MLflow …

  10. Manage model lifecycle in Unity Catalog - Azure Databricks

    Learn how to manage the lifecycle of MLflow Models in Unity Catalog. Learn how to migrate workflows and models in the Workspace Model Registry to Unity Catalog.