I played a bit around with Azure ML studio. So as I understand the process goes like this:
a) Create a training experiment. Train it with data.
b) Create a Scoring experiment. This will include the trained model from the training experiment. Expose this as a service to be consumed over REST.
Maybe a stupid question but what is the recommended way to get the complete experience like the one i get when I use an app like https://datamarket.azure.com/dataset/amla/mba (Frequently Bought Together API built with Azure Machine Learning).
I mean the following:
a) Expose 2 or more services - one to train the model and the other to consume (test) the trained model.
b) User periodically sends training data to train the model
c) The trained model/models now get saved available for consumption
d) The user is now able to send a data frame to get the predicted results.
Is there an additional wrapper that needs to be built?
If there is a link documenting this please point me to the same.
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