Guideline in Migrating Microsoft Machine Learning Studio (Classic) to Azure Machine Learning (AML)
ML Studio (classic) documentation is being retired and may not be updated in the future
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In the early days of Microsoft Cloud, Microsoft launched two product offerings relevant to Machine Learning Development: Azure Machine Learning and Azure Machine Learning Studio (Classic). On some occasion, there was another tool called Azure ML Workbench to help prepare data, develop experiments, and deploy models at cloud scale. With all these complex, redundant terminologies, it caused confusion…Now, it’s all unified and merged under “Azure Machine Learning (AML)”.
In short, these are going to be retired by 31 August 2024.
Azure Machine Learning now provides rich, consolidated capabilities for model training and deploying, we’ll retire the older Machine Learning Studio (classic) service on 31 August 2024. Please transition to using Azure Machine Learning by that date. From now through 31 August 2024, you can continue to use the existing Machine Learning Studio (classic). Beginning 1 December 2021, you won’t be able to create new Machine Learning Studio (classic) resources.
The below table summarizes the key difference between the two:
In my view, it’s more advantageous for organizations to move to the new portal and leverage the full power of cloud computing. GPU support. MLOps capability. ML Pipeline. The downside is the cost, which was free in the earlier version, but I want to capitalize on the capabilities that come with Azure ML, which are much richer in functionalities and efficient overall.
Personally, I don’t think it’s a big shift in terms of experience because data experts could still use the drag-and-drop feature in the…
