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Web services created using the Classic deployment model and web services created using the New Azure Resource Manager deployment model are listed in the Microsoft Azure Machine Learning Web Services portal.Classic web services are also listed in Machine Learning Studio on the Web services tab. Machine Learning web services provide an interface between an application and a Machine Learning workflow scoring model.

For larger amounts of data, transfer it to Azure Storage first, and then use the Import Data module to bring it into your experiment. You can learn about image input capability in the Import Images reference.

For more information, see Extend your experiment with R and Execute Python machine learning scripts in Azure Machine Learning Studio.

Is it possible to use something like PMML to define a model?

The sample code is available on: You can also use the sample Microsoft Excel workbook that's created for you and is available in the web service dashboard in Machine Learning Studio.

What are the main updates to Azure Machine Learning?

The algorithm, data source, data format, or data transformation operation that I am looking for isn't in Azure Machine Learning Studio. You can go to the user feedback forum to see feature requests that we are tracking.

Add your vote to a request if a capability that you're looking for has already been requested.No, Predictive Model Markup Language (PMML) is not supported.You can use custom R and Python code to define a module.If a module takes more than one input, the 10 GB value is the total of all input sizes.You can also sample larger datasets by using queries from Hive or Azure SQL Database, or you can use Learning by Counts preprocessing before ingestion.Here are some frequently asked questions (FAQs) and corresponding answers about Azure Machine Learning, a cloud service for developing predictive models and operationalizing solutions through web services.