Combining Simulation and Machine Learning

This webinar shows how the different predictive abilities of simulation and machine learning combine to advance decision support in business and public enterprise. Info and links below ⬇ 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 pipeline. Agenda: 00:00 Introduction to H2O Driverless AI Technology 03:12 Simulation Modeling vs. Machine Learning 10:58 Simulation Modeling + Machine Learning 19:01 Basics of H2O driverless AI; predicting patient stay example 28:43 Hospital capacity planning using multi-method modeling and machine learning 37:26 Process of incorporating a trained ML model (AI MOJO Pipeline) into an AnyLogic model 42:24 Q&A Q&A PDF - www.anylogic.com/upload/webinars/anylogic-h2o-webi… Presented by: Arash Mahdavi, AI Program Lead, The AnyLogic Company Niki Athanasiadou, Data Scientist, H2O.ai Heman Kapadia, Senior Solution Architect, H2O.ai AnyLogic and H2O demo models - www.anylogic.com/features/artificial-intelligence/… H2O platform - www.h2o.ai/try-driverless-ai/ AnyLogic Simulation Platform - www.anylogic.com/?utm_source=youtube&utm_medium=so… Facebook - www.facebook.com/AnyLogicCo/ LinkedIn - www.linkedin.com/company/the-anylogic-company Twitter - twitter.com/anylogicco #AnyLogic #Simulation #MachineLearning

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