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Azure Machine Learning

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Build, train, and deploy models from a central platform
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Azure Machine Learning is a comprehensive ML platform that centralizes building, training, fine-tuning, and deploying machine learning and language models. It provides tools and integrations to manage model lifecycle, deploy endpoints, and integrate models into applications.

Key Features:

  • Azure Machine Learning Studio: centralized workspace for artifacts, experiments, and deployments
  • Language model fine-tuning, training, and deployment capabilities with model catalog support
  • Integration with Azure OpenAI Service, RESI APIs, and other Azure services (Key Vault, Blob Storage, Container Registry)

Use Cases:

  • End-to-end model development and MLOps for production ML workflows
  • Fine-tuning and deploying large language models as endpoints for applications
  • Integrating and managing models across applications using RESI APIs and Azure service ecosystem

Benefits:

  • High availability with a 99.9% SLA
  • Centralized collaboration and lifecycle management for data scientists and developers
  • No additional charge for Azure Machine Learning itself; pay only for consumed Azure services and compute
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