H2O Driverless AI automates time-consuming ML tasks so that data scientists can work faster and more efficiently. Automated tasks include: model validation, model tuning, model selection, and feature engineering.
In this webinar we showcase how to improve the predictive capability of a model by embedding an H2O Driverless AI MOJO (Model Object, Optimized) pipeline.
Webinar agenda:
In this webinar we showcase how to improve the predictive capability of a model by embedding an H2O Driverless AI MOJO (Model Object, Optimized) pipeline.
Webinar agenda:
- Introduction to H2O Driverless AI Technology
- Simulation Modeling vs. Machine Learning
- Simulation Modeling + Machine Learning
- Basics of H2O driverless AI; predicting patient stay example
- Hospital capacity planning using multi-method modeling and machine learning
- Process of incorporating a trained ML model (AI MOJO Pipeline) into an AnyLogic model
- Q&A (extended follow-up Q&A PDF)
Find out more about using AnyLogic simulation and the H2O.ai Driverless AI platform on our dedicated H2O.ai page.
