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”.
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.
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