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Building an Interpretable & Deployable Propensity AI/ML Model in 7 Steps…

To start with, you may have a tabular data set with a combination of: Dates/Timestamps Categorical Values Text strings Numeric Values A business sponsor wants to build a Propensity to Buy model from historical data.How many Steps does it take? Let’s find out. We are going to use H2O’s Driverless AI instance with 1 GPU (optional...

Read more Automatic Machine Learning on Red Hat OpenShift Container Platform Delivers Data Science Ease and Flexibility at Scale
by Vinod Iyengar | May 14, 2019 Cloud , Data Science , Demos , H2O Driverless AI

Last week at Red Hat Summit in Boston, Sri Ambati, CEO and Founder, demonstrated how to use our award-winning automatic machine learning platform, H2O Driverless AI , on Red Hat OpenShift Container Platform. You can watch the replay here .What we showed not only helps data scientists achieve results, it also enables them to scale their ...

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AI/ML Projects — Don’t get stymied in the last mile

Data Scientists build AI/ML models from data, and then deploy it to production – in addition to a plethora of tasks around data insights, data cleansing etc., Part of the Data Scientist job description/requirement is making models available for transparency, auditability as well as explainability for both regulators as well as internal bu...

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Drink in the Data with H2O at Strata SJ 2016
by Team | March 21, 2016 Community , Demos , Events

It’s about to rain data in San Jose when Strata + Hadoop World comes to town March 29 – March 31st. H2O has a waterfall of action happening at the show. Here’s a rundown of what’s on tap. Keep it handy so you have less chance of FOMO (fear of missing out). Hang out with H2O at Booth #1225 to learn more about how machine learning can hel...

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Databricks and H2O Make it Rain with Sparkling Water
by Team | December 01, 2015 Demos , Sparkling Water

**This blog post was first posted on the Databricks blog hereDatabricks provides a cloud-based integrated workspace on top of Apache Spark for developers and data scientists. has been an early adopter of Apache Spark and has developed Sparkling Water to seamlessly integrate’s machine learning library on top of Spark. In thi...

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