MLflow API reference

Articol
01.03.2024

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 Learning provides a managed version of the MLflow server, which includes experiment tracking and the Model Registry.

For MLflow, there are two REST API reference guides:

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Documentație

Build dashboards with the MLflow Search API - Azure Databricks

Learn how to build dashboards of aggregate metrics with the MLflow Search API
Workspace Model Registry webhooks - Azure Databricks

Learn about Workspace Model Registry webhooks in Azure Databricks. Listen for Model Registry events so your integrations can automatically trigger actions.
View training results with MLflow runs - Azure Databricks

Learn how to use MLflow runs to view and analyze the results of a model training experiment, and how to manage and organize runs.
Access the MLflow tracking server from outside Azure Databricks - Azure Databricks

Learn how to access the MLflow tracking server from outside Azure Databricks to log your MLflow application’s data.
Organize training runs with MLflow experiments - Azure Databricks

Learn how to create and manage experiments to organize your machine learning training runs in MLflow.
Track model development using MLflow - Azure Databricks

Learn about experiments and tracking machine learning training runs automatically using MLflow.
Databricks Autologging - Azure Databricks

Learn about Azure Databricks Autologging with MLflow, a no-code solution that extends MLflow’s automatic logging solution to track your machine learning training experiments.
MLflow for gen AI agent and ML model lifecycle - Azure Databricks

Learn how Databricks uses MLflow to manage the end-to-end machine learning lifecycle.

Instruire

Modul

Use MLflow in Azure Databricks - Training

Learn how to use MLflow in Azure Databricks to track machine learning experiments and deploy models.

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Microsoft Certified: Azure Data Scientist Associate - Certifications

Gestionați ingestia și pregătirea datelor, instruirea și implementarea modelelor și monitorizarea soluțiilor de învățare programată cu Python, Azure Machine Learning și MLflow.

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MLflow API reference

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