How a Machine Learning model progresses from an experiment to an operationalized web service

An experiment is a canvas in Azure Machine Learning Studio that allows you to interactively develop, run, test, and iterate as you create a predictive analysis model. A wide variety of modules are available that you can use to bring data into your experiment, manipulate the data, train a model using machine learning algorithms, score the model, evaluate the results, and output final values. Once you’re satisfied with your experiment, you can deploy it as an Azure web service so that users can send it new data and receive back results. In this article we’ll give an overview of the mechanics of how your Machine Learning model progresses from a development experiment to an operationalized web service. While Azure Machine Learning Studio is designed primarily to help you develop and…


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