Google Prediction API graduates from labs, adds new features

By Zachary Goldberg, Product Manager

Since the general availability launch of the Prediction API this year at Google I/O, we have been working hard to give every developer access to machine learning in the cloud to build smarter apps. We’ve also been working on adding new features, accuracy improvements, and feedback capability to the API. Today we take another step by announcing Prediction v1.4. With the launch of this version, Prediction is graduating from Google Code Labs, reflecting Google’s commitment to the API’s development and stability. Version 1.4 also includes two new features:

• Data Anomaly Analysis
• One of the hardest parts of building an accurate predictive model is gathering and curating a high quality data set. With Prediction v1.4, we are providing a feature to help you identify problems with your data that we notice during the training process. This feedback makes it easier to build accurate predictive models with proper data.
• PMML Import
• PMML has become the de facto industry standard for transmitting predictive models and model data between systems. As of v1.4, the Google Prediction API can programmatically accept your PMML for data transformations and preprocessing.
• The PMML spec is vast and covers many, many features. You can find more details about the specific features that the Google Prediction API supports here.

We’re looking forward to seeing what you create with these new capabilities!

Feel free to find us and ask questions about these new features on our discussion group or submit feedback via our feedback form.


Zachary Goldberg is Product Manager for the Google Prediction API. He has a strange fascination with the Higgs Boson.

Posted by Scott Knaster, Editor