Model deployment
After you are happy with a particular model, save it as a trained model and then prepare an experiment for a web service and proceed to deploy the model. Refer to Chapter 11, Publishing a Model as a Web Service, to find the details on how to deploy a model to the staging environment and test it visually in ML Studio.
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