Retraining and Updating Azure Machine Learning models with Azure Data Factory

Monday, November 9, 2015Customers working with Azure Machine Learning models have been leveraging the built in AzureMLBatchExecution activity with Azure Data Factory pipelines to operationalize the ML models in production and score new data against the pre-trained models at scale. But as trends and variables that influence the model’s parameters change over time, ideally this pipeline should also support recurring automated retraining and updates to the model with latest training data. Now Azure Data Factory allows you to do just that with the newly released AzureMLUpdateResource activity. With Azure ML you typically first setup your scoring and training experiments, then two separate web service endpoints for each experiment. Next, you can use the AzureMLBatchExecution activity with Data Factory to do both scoring of incoming data against the latest model hosted…


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