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Use an enterprise-grade AI service for the end-to-end machine learning (ML) lifecycle.
OVERVIEW
- Streamline prompt engineering and ML model workflows. Accelerate model development with powerful AI infrastructure.
- Reproduce end-to-end pipelines and automate workflows with continuous integration and continuous delivery (CI/CD).
- Unify data and AI governance with built-in security and compliance. Run compute anywhere for hybrid machine learning.
- Gain visibility into models and evaluate language model workflows. Mitigate fairness, biases, and harm with built-in safety system.
FEATURES
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 Microsoft, OpenAI, Hugging Face, Meta, Cohere and more 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
Azure Machine Learning supports extensive, diverse capabilities for robust AI and ML development.
MLOps
Collaborate and streamline model management with machine learning operations (MLOps).
Security
34,000
Full-time equivalent engineers dedicated to security initiatives at Microsoft.
15,000
Partners with specialized security expertise.
>100
Compliance certifications, including over 50 specific to global regions and countries.
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.
Discover the latest features and announcements from Azure Machine Learning.
CUSTOMER STORIES
RESOURCES
Tutorial
Azure Machine Learning in a day
Learn how to get started with Azure Machine Learning.
Tutorial
Machine learning pipelines
Create production machine learning pipelines with the Python SDK.
Tutorial
No-code classification models
Train a classification model with no-code automated machine learning in the Azure Machine Learning studio.
Tutorial
Machine learning operations
Explore end-to-end machine learning operations (MLOps) with Azure Machine Learning.
Tutorial
Compute-intensive models
Train compute-intensive models with Azure Machine Learning.
Videos
Deep learning containers
Learn about deep learning containers with PyTorch and Azure Machine Learning.
Videos
Managed online endpoints
Learn about managed online endpoints, now generally available in Azure Machine Learning.
Tutorial
Labeling made easy
Label images and text documents using assisted machine learning for data labeling tasks.
Resource
What is machine learning?
Learn about the science of training machines to analyze and learn from data the way humans do.
Resource
Machine learning algorithms
An introduction to the math and logic behind machine learning.
Resource
Open-source machine learning
Learn what open-source machine learning is and explore open-source machine learning projects, platforms, and tools.
Webinar
Uncover predictive Insights with analytics and AI
Learn how to bring analytics and machine learning together to grow your business agility.
Frequently asked questions
- The service is available in several Azure regions, with more on the way.
- The SLA for Azure Machine Learning is 99.9 percent uptime.
- Azure Machine Learning studio is the top-level resource for Azure Machine Learning. This capability provides a centralized place for data scientists and developers to work with all the artifacts for building, training, and deploying machine learning models.
- Azure Machine Learning is a comprehensive machine learning platform that supports language model fine-tuning and deployment. Using the Azure Machine Learning model catalog, users can create an endpoint for Azure OpenAI Service and use RESI APIs to integrate models into applications.
- There's no additional charge to use Azure Machine Learning. However, along with compute, you will incur separate charges for other Azure services consumed, including but not limited to Azure Blob Storage, Azure Key Vault, Azure Container Registry, and Azure Application Insights. See pricing details.
Next steps
Choose the Azure account that’s right for you
Pay as you go or try Azure free for up to 30 days.
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