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What is the difference between Azure Machine Learning Studio and Azure Machine Learning Workbench? What is the intended difference? And is it expected that Workbench is heading towards deprecation in favor of Studio?
I have gathered an assorted collection of differences:
However, I have also found several scattered references claiming that Studio is a renamed updated of Workbench, even though both services appear to still be offered.
For a fresh Data Scientist looking to adopt the Microsoft stack (potentially on an enterprise scale within the medium-term and for the long-term), which offering should I prefer?
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Azure Machine Learning is a cloud service for accelerating and managing the machine learning project lifecycle. Machine learning professionals, data scientists, and engineers can use it in their day-to-day workflows: Train and deploy models, and manage MLOps.
ML Studio (classic) does not support Code SDKs, ML pipeline, Automated model training and has a basic model for MLOPs and many other features were missing that is a part of Azure Machine Learning Studio now.
Azure Blockchain Workbench provides a web application and REST APIs for managing blockchain applications and users. Blockchain Workbench administrators can manage application access and assign your users to application roles. Azure AD users are automatically mapped to members in the application.
Machine Learning Workbench (MLW) is aimed at data scientists and machine learning practitioners to help them solve business problems faster by streamlining the machine learning lifecycle including data capture and analysis, model training and evaluation, and model deployment.
Azure Machine Learning Workbench is a preview downloadable application. It provides a UI for many of the Azure Machine Learning CLI commands, particularly around experimentation submission for Python based jobs to DSVM or HDI. The Azure Machine Learning CLI is made up of many key functions, such as job submisison, and creation of real time web services. The workbench installer provided a way to install everything required to participate in the preview.
Azure Machine Learning Studio is an older product, and provides a drag and drop interface for creating simply machine learning processes. It has limitations about the size of the data that can be handled (about 10gigs of processing). Learning and customer requests have based on this service have contributed to the design of the new Azure Machine Learning CLI mentioned above.
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It should be added that Azure Machine Learning Workbench is deprecated since september 2018 and has been replaced by the Azure Machine Learning services, which was made generally available in december 2018. The core functionality is still intact, but some major changes to point out about the architecture are:
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