Webinar 008 E. LeDell - Scalable Automatic Machine Learning in R with H2O AutoML

Speaker: Erin LeDell
Title: Scalable Automatic Machine Learning in R with H2O AutoML
Bio + Abstract: Below!
Stream: https://www.youtube.com/watch?v=DjzKTeIIxOY&feature=youtu.be

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• date: every Thursday 8:00 pm GMT+2 (starting April 2nd!)
• format: one 45 minutes long stream + 10 minutes for Q&A
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Abstract:
The focus of this presentation is scalable and automatic machine learning in R using the H2O machine learning platform. H2O is an open source, distributed machine learning platform is designed to scale to very large datasets that may not fit into RAM on a single machine. We will provide a brief overview of the field of Automatic Machine Learning, followed by a detailed look inside H2O's AutoML algorithm. H2O AutoML provides an easy-to-use interface which automates data pre-processing, training and tuning a large selection of candidate models (including multiple stacked ensemble models for superior model performance), and due to the distributed nature of the H2O platform, H2O AutoML can scale to very large datasets. The result of the AutoML run is a "leaderboard" of H2O models which can be easily exported for use in production.

Biogram:
Dr. LeDell is the Chief Machine Learning Scientist at H2O.ai, the company that produces the open source, distributed machine learning platform, H2O. Before joining H2O.ai, she was the Principal Data Scientist at two AI startups (both acquired), the founder of DataScientific, Inc. and a software engineer at a large consulting firm. She received her Ph.D. from UC Berkeley where her research focused on machine learning and computational statistics. She also holds a B.S. and M.A. in Mathematics. Erin has founded Women+ in Machine Learning & Data Science and co-founded R-Ladies Global.