Google Prediction API 1.5 adds enumeration, analysis, and more

Google's Prediction API 1.5 introduces several enhancements aimed at improving user experience and functionality, including model enumeration and analysis. Users can now list all models with the trainedmodels.list request and gain detailed insights into data and models through the trainedmodels.analyze request, which provides information such as output values and confusion matrices. The update also simplifies the trainedmodels.get request by offering a more straightforward model description and including timestamps for better tracking of the model lifecycle. Additionally, new sample applications for Google App Engine, written in Python and Java, demonstrate how to utilize the Prediction API, including managing OAuth 2.0 credentials and making predictions. The release is accessible via the HTTP RESTful interface and client libraries, with an interactive experience available through the Google APIs Explorer.

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