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Choosing between Microsoft Azure Machine Learning Studio vs Azure Machine Learning Services

This post compares different features of Microsoft Azure Machine Learning Studio and Azure Machine Learning Services to help you choose the right product to develop your machine learning solutions most effectively. It also compares the recently introduced Azure ML Service/Visual Interface (preview) features.

With Microsoft introducing a number of services around Machine Learning/AI, this post compares the major features of Azure Machine Learning Studio and Azure Machine Learning Services. Microsoft has recently announced a preview for “Visual Interface” as a part of Azure Machine Learning Services.

Azure Machine Learning Service is available in two flavors, a python SDK(GA) and a drag-drop style “Visual Interface”.

AMLStudio_vs_AMLServices_FeatureComparison

The following are few major points to decide between the two :

Azure Machine Learning Services

  • Hybrid training/scoring gives the flexibility to train locally and deploy the trained model on the cloud or vice versa
  • Ability to deploy the trained model as close to the scoring data event as possible
  • Freedom to use any framework, compute power, tools available
  • Auto ML and Auto Hyper Parameter tuning options

Azure Machine Learning Studio

  • Easy for beginners/developers/data scientists who need a quick hands on feel
  • Standard experiments but quick results in lesser time
  • Fully managed service with less control and no on-premise options

Note: Azure Machine Learning WorkBench has been deprecated

I hope this post has helped you get a better understanding about the Microsoft Azure Machine Learning offerings. Follow our upcoming blogs to know more about Data and AI using Microsoft Stack.

Kind Regards,
Sriram

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