Azure Machine Learning service
Build models rapidly and operationalize at scale from cloud to edge
Accelerate the end-to-end machine learning lifecycle
Streamline the building, training, and deployment of machine learning models. Bring machine learning models to market faster using the tools and frameworks of your choice, increase productivity using automated machine learning, and innovate on a secure, enterprise-ready platform.
Thoughtful Machine Learning with Python
Develop platform-based, high-quality machine learning models using open-source tools and frameworks with Azure.
Simplified machine learning with powerful, no-code, automated machine learning capabilities and open-source support
Robust DevOps for machine learning that integrates with your existing DevOps processes and helps manage the complete machine learning lifecycle
Scale on demand from your desktop, and build and deploy machine learning models anywhere, from cloud to edge
Enterprise-ready Azure security, control, and governance to help protect your infrastructure and capabilities
Access simplified machine learning
Rapidly build and deploy machine learning models using tools that meet your needs across skill levels, from no-code to code-first experiences. Use a visual drag-and-drop interface, a hosted notebook environment, or automated machine learning. Accelerate model development with automated feature engineering, algorithm selection, and hyperparameter sweeping. Get built-in support for familiar open-source tools and frameworks, including ONNX, Python, PyTorch, scikit-learn, and TensorFlow.
Innovate faster with robust MLOps
MLOps—DevOps for machine learning—streamlines the end-to-end lifecycle, from data preparation to deployment and monitoring. Simplify your workflows and increase efficiency using machine learning pipelines. Take advantage of continuous integration and continuous delivery (CI/CD) for ease of support and maintenance while improving model quality over time. Manage your model artifacts from a central portal, and monitor the performance of deployed models.
Tap into the cloud on demand from your desktop
Use any data and deploy machine learning models anywhere, from the cloud to the edge, to maximize flexibility. Train models quickly and cost-effectively by autoscaling using powerful CPU and GPU compute resources. Inference in real time in the cloud or at the edge using FPGAs.
Protect your infrastructure and solutions
Build your machine learning models using the enterprise-ready security, compliance, and virtual network support of Azure for all your data science needs. Protect your workloads using built-in controls for identity, data, and networking across Azure, which offers the most comprehensive compliance portfolio of any cloud provider.
Pay only for what you need, with no upfront cost
Pay only for the Azure resources you need for a limited time. For more details, including the cost of deploying models, see the Azure Machine Learning service pricing page.
How to use Azure Machine Learning service
Create a workspace
Build and train
Deploy and manage
Getting Started Resources
Start using Azure Machine Learning service today
Customers using Azure Machine Learning service
Azure updates, blogs, and announcements
Frequently asked questions about Azure Machine Learning service
The service is generally available in several countries/regions, with more on the way.
The service-level agreement (SLA) for Azure Machine Learning service is 99.9 percent.
The Azure Machine Learning service workspace is the top-level resource for the service. It provides a centralized place to work with all the artifacts you create.