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Enterprise-grade machine learning service to build and deploy models faster.

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Accelerate the end-to-end machine learning lifecycle

Empower data scientists and developers with a wide range of productive experiences to build, train, and deploy machine learning models and foster team collaboration. Accelerate time to market with industry-leading MLOps—machine learning operations, or DevOps for machine learning. Innovate on a secure, trusted platform, designed for responsible machine learning.

1

Machine Learning for all skill levels

Productivity for all skill levels, with Jupyter Notebooks, drag-and-drop designer, and automated machine learning.

2

End-to-end MLOps

Robust MLOps capabilities that enable creation and deployments of models at scale using automated and reproducible machine learning workflows.

3

Responsible machine learning innovation

Rich set of built-in responsible capabilities to understand, protect, and control data, models, and processes.

4

Open and interoperable

Best-in-class support for open-source frameworks and languages including MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R.

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Advanced security, governance, and hybrid infrastructure

Create extraordinary experiences for all of your customers—whether they’re right next door or on the other side of the world. With datacenters in more global regions, the largest compliance portfolio of any cloud provider, and a bold commitment to sustainability, you don’t need to choose between quantity and quality when you build on Azure.

Want to see it in action?

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