Webinar: Combining Simulation and Machine Learning

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:
  • 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.

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