Scalable Automatic Machine Learning with H2O
Details
Hello Makers!
Please joins us as we discuss Scalable Automatic Machine Learning with H2O!
*****Please RSVP on this Eventbrite link to register:
https://www.eventbrite.com/e/scalable-automatic-machine-learning-with-h2o-tickets-77622921247
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Following is a brief agenda for the program:
9:30am - 10:00 am: Breakfast & Networking
10:00am - 11:15am: Parul’s Talk
11:15am - 11:45am: Q&A
12 noon - Event ends
In this presentation, Parul Pandey, will provide a history and overview of the field of “Automatic Machine Learning” (AutoML), followed by a detailed look inside H2O’s open source 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.
Parul's Bio:
Parul is a Data Science Evangelist here at H2O.ai. She combines Data Science, evangelism and community in her work. Her emphasis is to spread the information about H2O and Driverless AI to as many people as possible, She is also an active writer and has contributed towards various national and international publications.