Past Meetup

#Hors-série - Paris WiMLDS & Paris ML Meetup

This Meetup is past

110 people went

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The Women in Machine Learning & Data Science (WiMLDS) meetup and the Paris Machine Learning Group are hosting an exceptional “hors-série” meetup featuring Erin LeDell & Joe Chow.

The venue can welcome 90 people. Please make sure to subscribe only if you know you will attend.

The meetup will be live streamed for those who can’t be there.


19:30 – Introduction by Ingima & the Paris WiMLDS + Paris ML Group teams


19:40 – “Scalable Automatic Machine Learning with H2O” by Erin LeDell, Chief Machine Learning Scientist at

This presentation will provide a history and overview of the field of Automatic Machine Learning (AutoML), 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). The result of the AutoML run is a "leaderboard" of H2O models which can be easily exported for use in production. AutoML is available in all H2O interfaces (R, Python, Scala, web GUI) and due to the distributed nature of the H2O platform, can scale to very large datasets. The presentation will end with a demo of H2O AutoML in R and Python, including a handful of code examples to get you started using automatic machine learning on your own projects.

Dr. Erin LeDell is the Chief Machine Learning Scientist at Erin has a Ph.D. in Biostatistics with a Designated Emphasis in Computational Science and Engineering from University of California, Berkeley. Her research focuses on automatic machine learning, ensemble machine learning and statistical computing. She also holds a B.S. and M.A. in Mathematics. Before joining, she was the Principal Data Scientist at (acquired by GE Digital in 2016) and Marvin Mobile Security (acquired by Veracode in 2012), and the founder of DataScientific, Inc.

20:35 – “The Making of a Real-World Moneyball Application - Finding Undervalued Players with H2O AutoML, LIME and Shiny” by Joe Chow, Data Science Evangelist & Community Manager at

Joe Chow ( recently teamed up with IBM and Aginity to create a proof of concept "Moneyball" app for the IBM Think conference in Vegas. The original goal was just to prove that different tools (e.g. H2O, Aginity AMP, IBM Data Science Experience, R and Shiny) could work together seamlessly for common business use-cases. Little did Joe know, the app would be used by Ari Kaplan (the real "Moneyball" guy) to validate the future performance of some baseball players. Ari recommended one player to a Major League Baseball team. The player was signed the next day with a multimillion-dollar contract. This talk is about Joe's journey to a real "Moneyball" application.

20:50 Networking / Cocktail

During the event, you can share content using #WiMLDSParis & @WiMLDS_Paris or #ParisML & @ParisMLgroup

After the meet-up, the video will be share on : &

Host information :

The room can welcome 90 people. First arrived, first served!
Keep in mind the session will be streamed.
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