Azure Machine Learning

OVERVIEW

Build business-critical ML models at scale

Streamline prompt engineering and ML model workflows. Accelerate model development with powerful AI infrastructure.

Learn about prompt flow
Reproduce end-to-end pipelines and automate workflows with continuous integration and continuous delivery (CI/CD).

Learn about ML operations
Unify data and AI governance with built-in security and compliance. Run compute anywhere for hybrid machine learning.

Learn about built-in security
Gain visibility into models and evaluate language model workflows. Mitigate fairness, biases, and harm with built-in safety system.

Learn about responsible AI

FEATURES

Take advantage of key features for the full ML lifecycle

Data preparation

Quickly iterate data preparation on Apache Spark clusters within Azure Machine Learning, interoperable with Microsoft Fabric.

Feature store

Increase agility in shipping your models by making features discoverable and reusable across workspaces.

AI infrastructure

Take advantage of purpose-built AI infrastructure uniquely designed to combine the latest GPUs and InfiniBand networking.

Automated machine learning

Rapidly create accurate machine learning models for tasks including classification, regression, vision, and natural language processing.

Responsible AI

Build responsible AI solutions with interpretability capabilities. Assess model fairness through disparity metrics and mitigate unfairness.

Model catalog

Discover, fine-tune, and deploy foundation models from OpenAI, Hugging Face, and Meta using the model catalog.

Prompt flow

Design, construct, evaluate, and deploy language model workflows with prompt flow.

Managed endpoints

Operationalize model deployment and scoring, log metrics, and perform safe model rollouts.

Capabilities

Explore how to bring ML to production

Azure Machine Learning supports extensive, diverse capabilities for robust AI and ML development.

Generative AI

Streamline prompt engineering projects and build language model–based applications.

Learn more

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Automated ML

Automatically build machine learning models with speed and scale.

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MLOps

Collaborate and streamline model management with machine learning operations (MLOps).

Learn more

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Responsible AI

Develop, use, and oversee AI solutions responsibly with Azure AI.

Learn more

Built-in security and compliance

Learn more about security on Azure

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Pricing

Pay only for what you need, with no upfront cost

Use Azure Machine Learning with no extra cost. Charges apply only for the underlying compute resources utilized during model training or inference. You have the flexibility to select from a diverse range of machine types, spanning categories such as general-purpose CPUs and specialized GPUs.

See pricing

What’s new in Azure Machine Learning

 Discover the latest features and announcements from Azure Machine Learning.

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CUSTOMER STORIES

Customers are innovating with Azure Machine Learning

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“It’s been very valuable to us to work with Microsoft as we enhance and expand Pi because the reliability and scale of Azure AI infrastructure is among the best in the world.”

Mustafa Suleyman, Cofounder and Chief Executive Officer, Inflection AI

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“Our teams usually test [data], get results, and then use it to develop models and algorithms, which we then build into software products. This platform makes the entire process simpler, faster, and more streamlined.”

Mogens Mikkelsen, Enterprise Architect, SEGES Innovation

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“Marks & Spencer has more than 30 million customers and large amounts of data that require systems that can scale to process it. Azure Machine Learning allows us to build machine learning solutions that can scale and give customers the right offers and better service overall.”

Luis Arnedo Martinez, Machine Learning Platform Product Manager, Marks & Spencer

“With Azure Machine Learning, we can show the patient a risk score that is highly tailored to their individual circumstances. …Ultimately, we aim to reduce risk, reduce uncertainty, and improve surgical outcomes.”

Professor Mike Reed, Clinical Director, Trauma and Orthopedics, Northumbria Healthcare NHS Foundation Trust

“Microsoft Azure perfectly complements our digital ecosystem to help deliver the best possible fan experiences for the world's best sports league.”

Miguel Ángel Leal, Chief Technology and Innovation Officer, LALIGA

“Using Azure Machine Learning, we can train a model on multiple distributed datasets. Rather than bringing the data to a central point, we do the opposite. We send the model for training to the participants’ local compute and datasets at the edge and fuse the training results in a foundation model.”

Johan Bryssinck, AI/ML Product and Program Management Lead, Swift