Google releases V1.2 of Google Prediction API

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To join the preview group, go to the APIs Console and click the Prediction API slider to “ON,” and then sign up for a Google Storage account.

For the past several months, I have been member of a semi-public beta test/group/forum – that is headed by Travis Green of the Google Prediction API Team (not the hockey player). Basically in helping the Google guys more feedback on the feature list for model building via cloud computing. I couldn’t talk about it much , because it was all NDA hush hush.

Anyways- as of today the version 1.2 of Google Prediction API has been launched. What does this do to the ordinary Joe Modeler? Well it helps gives your models -thats right your plain vanilla logistic regression,arima, arimax, models an added ensemble option of using Google’s Machine Learning algorithms to give a tweak, a boost, a lift or a needle turn in your response rate.

And it is cloud supported, and encrypted for security. Heres the official link-

  • Chooses best technique from several available machine learning algorithms.
  • Supported inputs: numeric data and unstructured text.
  • Outputs hundreds of discrete categories, or continuous values.
  • Integrates with many platforms: Google App Engine, web and desktop apps, and command line.
  • v1.2 improvements:
  • Simpler interface: automatic data type detection, and score normalization.
  • Paid usage tier.
  • Improved usage monitoring and faster signup through the APIs Console.


What Can the Prediction API Do?

The Prediction API provides pattern-matching and machine learning capabilities. Given a set of data examples to train against, you can create applications that can perform the following tasks:

  • Given a user’s past viewing habits, predict what other movies or products a user might like.(so even if you didnt win the Netflix prize or are not Netflix- you can build a cutting edge propensity ensemble model without going to Phd school)
  • Categorize emails as spam or non-spam. (only relevant if you are Matt Cutts)
  • Analyze posted comments about your product to determine whether they have a positive or negative tone. (for custom apps in social media analysis)
  • Guess how much a user might spend on a given day, given his spending history.(spend models in retail and other domains)
Comments in Bold Italic are by me.

Anyways whats with the name- Prediction API ???

Author: Ajay Ohri

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