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I think saw a couple of differentiators from Google's prediction engine. Would someone happen to have a more comprehensive view of how this is different from Google Prediction API?

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The main difference between Google Prediction and Azure ML is that the former doesn't require any knowledge of machine learning algorithms, whereas the latter does. Google Prediction automatically selects the best algorithm based on the data you uploaded. In Azure ML, you have to choose an algorithm (and its parameters) yourself.

Other differences are that Azure also has a data transformation component, a built-in text analysis tool, it can perform clustering tasks, and it makes it easier to expose your trained models as APIs.

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