Azure Machine Learning
Use an enterprise-grade AI service for the end-to-end machine learning (ML) lifecycle
OVERVIEW
Build business-critical ML models at scale
- 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
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 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
Explore how to bring ML to production
Azure Machine Learning supports extensive, diverse capabilities for robust AI and ML development.
Security
Built-in security and compliance
Microsoft has committed to investing $20 billion in cybersecurity over five years.
We employ more than 8,500 security and threat intelligence experts across 77 countries.
Azure has one of the largest compliance certification portfolios in the industry.
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.
What’s new in Azure Machine Learning
Discover the latest features and announcements from Azure Machine Learning.
CUSTOMER STORIES
Customers are innovating with Azure Machine Learning
RESOURCES
Azure Machine Learning resources
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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