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The field of machine learning is an ever-changing and advancing landscape. For new and experienced machine learning (ML) practitioners alike, there is always more to learn. Learning and exploring are done in Azure, marrying new advancements with a sophisticated platform and toolset. Machine learning is not new to Azure, however. Azure Machine Learning Studio has been prevalent since 2015, providing a platform for the development and deployment of ML models from within a drag-and-drop UI. Today, the offerings have advanced and become even more integrated across services in Azure (VMs, AKS, Databricks, Storage, etc.). They provide more ways for developers and data scientists to develop, deploy, and monitor custom ML models with SDKs or by using an integrated drag-and-drop interface that needs very little coding. |
