Danger, Caution H2O steam is very hot!!

September 30, 2016
By

(This article was first published on R – Longhow Lam's Blog, and kindly contributed to R-bloggers)

blog_steam

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.

blogcode

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.

blogsteam2

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.

blogsteam3

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!

To leave a comment for the author, please follow the link and comment on their blog: R – Longhow Lam's Blog.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Search R-bloggers


Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)