R Ladies Edinburgh: [ONLINE] Scalable Automatic Machine Learning in R with H2O with Erin LeDell

**UPDATE** We are moving this event online, at the same time and day. We will send a Zoom link for the call day prior to the event. Hope you can join us online!

Dr. Erin LeDell is the Chief Machine Learning Scientist at H2O.ai, where she leads the development of an open-source, automatic machine learning (AutoML) platform. Before joining H2O.ai, she worked as a data scientist and software engineer and founded DataScientific, Inc. She’s also the founder of the non-profit Women in Machine Learning & Data Science (WiMLDS.org) organization and co-founder of the R-Ladies Global organization. She received her Ph.D. from UC Berkeley where her research focused on machine learning and statistical computing.

**Scalable Automatic Machine Learning in R with H2O**

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 that 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. R code examples are available on GitHub for participants to follow along on their laptops.

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Q: Are men welcome to attend this event?
A: Our primary mission is to encourage more women and non-binary individuals to get involved in the R community. ***As such, we strongly encourage that all men who attend this event have a female or non-binary sponsor. Please contact mine@rladies.org if you have questions.***

Additionally, please help us by spreading the word about R-Ladies, and by being respectful of the fact that this event is primarily for women/non-binary/female-identifying individuals.

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