By Travis Green of the Google Prediction API
Team. If you’re looking
to make your app smarter and you think machine learning is more complicated than making three
API calls, then you’re reading the right blog post.
Today, we are
releasing v1.2 of the Google Prediction
API, which makes it even easier for preview users to build smarter apps by accessing
Google’s advanced machine learning algorithms through a RESTful web service.
Some technical details of the Prediction API:
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.
Ideas to make the most of the Prediction API:
Recommendation: What products might a user be interested in? (example)
Filter
RSS feeds, user comments, or feedback: Which posts are most relevant? Should a user comment be
featured? Which feedback should we look at first? (example)
Customize
homepages: Predict what content a user would like to see and populate the page with the user’s
anticipated interests.
Sentiment analysis: Is this comment positive or
negative? Does a commenter support Group A or Group B?
Message routing:
Route emails to the appropriate person based on analysis of the email
contents.
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.
We would also like to continue to thank our supportive preview users for
their help making the API the service it is today. We look forward to seeing many more of you
join us in making the web just a little bit smarter, and hearing your thoughts and feedback
through our discussion
group.
Travis Green's favorite part about his job
is designing smart applications. In his spare time, he is in the great outdoors (looking for
trouble).
