Tag Archives: Prediction API

Sample application illustrating use of the Google Prediction API within the Google App Engine environment


via GoogleCloudPlatform/prediction-try-java-python · GitHub.

Sample application illustrating use of the Google Prediction API within the Google App Engine environmentTry Prediction (v1.0)

This project provides a complete application illustrating use of the Google Prediction API within the Google App Engine environment. Sample code is provided for both the Java and Python App Engine runtimes, along with resources for CSS, Javascript, images and config data files, all of which are shared across the two runtime environments.

The application presents a simple interactive user experience: select a prediction model, enter a corresponding set of input text and submit your prediction request. For classification models, a graphical response is provided showing the confidence level for each category in the selected model. For regression models, a numerical result is presented.

The set of models supported and the corresponding input fields are entirely dynamic and controlled by a runtime text file (rc/models.json). You can freely add, change or remove models without changing any source code.

Web services in this domain typically provide access to a prediction model via a common set of shared security credentials. In this model, there is no need to force end users to perform the OAuth token granting sequence – authorization of end users is entirely up to the discretion of the application provider. This shared-server authorization model is one of the key elements being illustrated in this sample application.

You can try a live instance of this application at http://try-prediction.appspot.com.

Video: Why and How To Leverage Predictive APIs In Any Application


Louis Dorard of Codole discusses Machine Learning through the use of Prediction APIs: Providing examples of what can be done with them and what can be expected of ML in general. Looking at the various Prediction APIs available, how they work, and how they’re different from one another, from a developer and from a business perspective.

Last year, Forrester introduced the term “predictive apps” and described them as “the next big thing in app development” are “the next big thing in app development”. Fortunately for developers, machine learning is now being democratized through Prediction APIs that abstract away the complexities of building predictive models from data.