"In terms of time savings, it’s a standard practice for our team to use H2O for things like model evaluation, evaluating variable importances, and interpretability of the model. H2O just makes so much of that legwork so easy in our workflow. We have gotten so used to using H2O that it’s hard to imagine doing my job without it. We have gotten used to seeing things like data visualization, visualization of performance metrics in a model on the fly in H2O and Driverless AI, it’s hard to imagine being a data scientist and not use it. "Tate Campbell Data Scientist
- Claims Management
Overview of the Challenge
Verification of insurance claim audits with a machine learning setting to determine whether a certain diagnosis code was coded correctly or whether a hospital charge was billed correctly.