Danger, Caution H2O steam is very hot!!

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H2O has recently released its steam AI engine, a fully open source engine that support the management and deployment of machine learning models. Both H2O on R and H2O steam are easy to set up and use. And both complement each other perfectly.

A very simple example

Use H2O on R to create some predictive models. Well, due to lack of inspiration I just used the iris set to create some binary classifiers.

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Once these models are trained, they are available for use in the H2O steam engine. A nice web interface allows you to set up a project in H2O steam to manage and display summary information of the models.

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In H2O steam you can select a model that you want to deploy. It becomes a service with a REST API, a page is created to test the service.

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And that is it! Your predictive model is up and running and waiting to be called from any application that can make REST API calls.

There is a lot more to explore in H2O steam, but be careful H2O steam is very hot!


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