Exploring new possibilities for H2O at scale

Now, let's step through different ways we can integrate H2O at scale—the focus of this book—with the rest of the H2O AI Cloud platform and thereby achieve greater capabilities and value.

Leveraging H2O Driverless AI for prototyping and feature discovery

H2O's AutoML Driverless AI component is a highly automated model-building tool that uses (among other features) a genetic algorithm, AI heuristics, and exhaustive automated feature engineering to build accurate and explainable models— typically in hours—that are then deployed to production systems. Driverless AI, however, does not scale to train on the hundreds of GB to TBs sized datasets that H2O-3 and Sparkling Water handle.

It is quite useful, however, for data scientists to feed sampled data from these massive datasets to Driverless AI and then use the AutoML tool to (a) quickly prototype the model to gain an early understanding and (b...