"In Korea, resource of data scientists is shorter than the actual market needs. H2O AI Cloud solution met the requirements for both experienced and novice data scientists, with on-premises & cloud support."

"H2O.ai provides impressively scalable implementations of many of the important machine learning tools in a user-friendly environment. Allowing for free academic use sets a generous example for commercial software developers — it is also the way forward in the era of open-source software."

"Generally, at best, we could do things once a month or once a quarter. With H2O, things are more real time and a lot more faster. Rather than people spending resources, managing the databases and running the queries, they can spend time understanding the results and we can interpret it …

"There is no limit to scaling with H2O."

"H2O Sparkling Water allowed us to do rapid prototyping with a wide variety of algorithms."

"Driverless AI is a unique product because it solves so many problems in data science out-of-the-box."

"We reached 90% accuracy in the real-time deployment and our results were in-sync with the training phase, which was really good."

"I trained and scored on the entire data set, not a sample, and it was orders of magnitude faster than other tools. Kudos to H2O."

"With H2O we are able to build models quickly so we can find patterns that we can use right away."

"H2O has been a great partner for us for deploying Ignite solutions for some of our top clients."

"We use H2O and Spark for our bigger models. It is easy for us to deploy models with H2O."

"With H2O we saw how faster processing and faster access to data can help us and that we don't need to sample anymore."

"H2O has been the driver for building models at scale. We are talking about billions of claims. You can't do this with standard off the shelf open source techniques."

"The ability to do advanced analytics and do more work across the data is going to be the differentiator for insurance companies going forward."

“This was a huge win for our customers, and for the teams who are responding to these types of incidents. Even the most impressive results are not useful unless the team we are producing them for is able to take this information and actually use it. Having measurable results that …