Microsoft Azure Machine Learning

Microsoft Azure Machine Learning (Azure ML) is Microsoft's enterprise-grade cloud platform for end-to-end machine learning operations, enabling data scientists and ML engineers to build, train, deploy, and manage models at scale. Part of the Microsoft Azure cloud ecosystem, Azure ML provides a comprehensive MLOps environment with both code-first and low-code interfaces, supporting popular frameworks like TensorFlow, PyTorch, scikit-learn, and ONNX. The platform features Azure ML Studio for drag-and-drop model building, Automated ML for AutoML capabilities, Azure ML Designer for visual workflows, and MLOps integration with Azure DevOps for CI/CD pipelines. Azure ML excels at enterprise deployment with robust security, compliance, and governance capabilities including VNet isolation, private endpoints, managed identities, and certifications for ISO 27001, SOC 2, HIPAA, PCI DSS, and GDPR compliance. The platform provides scalable compute options from single-node training to distributed training across GPU clusters, with cost optimization through low-priority VMs and automatic scaling. Azure ML integrates seamlessly with Microsoft's broader AI stack including Azure Synapse Analytics for data warehousing, Azure Data Lake for storage, Power BI for visualization, and Azure Cognitive Services for pre-built AI models. Used by organizations like UPS, NBA, and Land O'Lakes for production AI applications, Azure ML offers responsible AI tools for model interpretability, fairness assessment, and bias detection, critical for enterprises prioritizing ethical AI deployment.