| title | description | services | documentationcenter | author | manager | editor | ms.assetid | ms.service | ms.workload | ms.tgt_pltfrm | ms.devlang | ms.topic | ms.date | ms.author |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Machine Learning What's New | Microsoft Docs |
New features that are available in Azure Machine Learning. |
machine-learning |
vDonGlover |
raymondl |
ddc716ed-2615-4806-bf27-6c9a5662a7f2 |
machine-learning |
data-services |
na |
na |
article |
10/05/2016 |
v-donglo |
- Classic Web services can now be managed in the new Microsoft Azure Machine Learning Web Services portal that provides one place to manage all aspects of your Web service.
- Which provides web service usage statistics.
- Simplifies testing of Azure Machine Learning Remote-Request calls using sample data.
- Provides a new Batch Execution Service test page with sample data and job submission history.
- Provides easier endpoint management.
- Web services are now managed as Azure resources managed through Azure Resource Manager interfaces, allowing for the following enhancements:
- There are new REST APIs to deploy and manage your Resource Manager based Web services.
- There is a new Microsoft Azure Machine Learning Web Services portal that provides one place to manage all aspects of your Web service.
- Incorporates a new subscription-based, multi-region web service deployment model using Resource Manager based APIs leveraging the Resource Manager Resource Provider for Web Services.
- Introduces new pricing plans and plan management capabilities using the new Resource Manager RP for Billing.
- You can now deploy your web service to multiple regions without needing to create a subscription in each region.
- Provides web service usage statistics.
- Simplifies testing of Azure Machine Learning Remote-Request calls using sample data.
- Provides a new Batch Execution Service test page with sample data and job submission history.
In addition, the Machine Learning Studio has been updated to allow you to deploy to the new Web service model or continue to deploy to the classic Web service model.