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 […]

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 […]

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 business use. While […]

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 […]

  **This blog post was first posted on the Databricks blog here Databricks provides a cloud-based integrated workspace on top of Apache Spark for developers and data scientists. H2O.ai has been an early adopter of Apache Spark and has developed Sparkling Water to seamlessly integrate H2O.ai’s machine learning library on top of Spark. In this […]