TL;DR - Azure ML
- Azure ML is Microsoft's cloud platform for building and deploying machine learning models
- It provides notebooks, AutoML, MLOps pipelines, and model management
- Pay for compute used, free tier for experimentation
Pricing: Paid only
Best for: Enterprises & professionals
Score: 85/100
Pricing Plans
free trialFree Tier
Free
Getting started
- Limited compute
- Managed notebooks
- AutoML
- Designer
Most Popular
Pay-As-You-Go
Varies
Usage-based
- All compute options
- MLOps pipelines
- Model management
- Endpoints
Enterprise
Custom
Advanced features
- Private endpoints
- Customer-managed keys
- Dedicated capacity
- Premium support
About Azure ML
Azure Machine Learning provides a complete platform for building, training, and deploying ML models. Notebooks for experimentation, automated ML for quick starts, and MLOps capabilities for production workflows.
Designer provides drag-and-drop model building. Responsible AI tools help understand model behavior. Deployment handles serving models at scale.
Data science teams on Azure use Azure ML as their end-to-end platform, from experimentation through production deployment.
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Azure ML FAQ
Free tier with limited compute for experimentation. Pay for compute instances, storage, and endpoints. Can get expensive for serious ML work.
Azure ML is Microsoft's enterprise ML platform. Build, train, and deploy models. Notebooks, AutoML, MLOps, and managed compute clusters.
Similar capabilities. Azure ML has better enterprise features and AutoML. SageMaker has more built-in algorithms. Choose based on your cloud.
AutoML automates model selection and hyperparameter tuning. Point it at data, get a trained model. Good for teams without deep ML expertise.
Yes, Azure ML has MLOps features: model registry, endpoints, pipelines, and monitoring. Deploy models to production with version control and CI/CD.