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H2O World 2017 has ended
Tuesday, December 5 • 2:02pm - 3:00pm
Driverless Hands-on focused on Machine Learning Interpretability - Patrick Hall, Navdeep Gill, Mark Chan - H2O.ai

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Patrick Hall is a senior director for data science products at H2o.ai where he focuses mainly on model interpretability. Patrick is also currently an adjunct professor in the Department of Decision Sciences at George Washington University, where he teaches graduate classes in data mining and machine learning. Prior to joining H2o.ai, Patrick held global customer facing roles and R & D research roles at SAS Institute. He holds multiple patents in automated market segmentation using clustering and deep neural networks. Patrick was the 11th person worldwide to become a Cloudera certified data scientist. He studied computational chemistry at the University of Illinois before graduating from the Institute for Advanced Analytics at North Carolina State University.

Navdeep is a Software Engineer/Data Scientist at H2O.ai. He graduated from California State University, East Bay with a M.S. degree in Computational Statistics, B.S. in Statistics, and a B.A. in Psychology (minor in Mathematics). During his education he gained interests in machine learning, time series analysis, statistical computing, data mining, & data visualization. Previous to H2O.ai he worked at Cisco Systems, Inc. focusing on data science & software development. Before stepping into industry he worked in various Neuroscience labs as a researcher/analyst. These labs were at institutions such as California State University, East Bay, University of California, San Francisco, and Smith Kettlewell Eye Research Institute. His work across these labs varied from behavioral, electrophysiology, and functional magnetic resonance imaging research. In his spare time Navdeep enjoys watching documentaries, reading (mostly non-fiction or academic), and working out.

Mark Chan is a hacker at H2O. He was previously in the finance world as a quantitative research developer at Thomson Reuters and Nipun Capital. He also worked as a data scientist at an IoT startup, where he built a web based machine learning platform and developed predictive models. Mark has a MS Financial Engineering from UCLA and a BS Computer Engineering from University of Illinois Urbana-Champaign. In his spare time Mark likes competing on Kaggle and cycling.

Enjoy the slides: https://www.slideshare.net/0xdata/driverless-ai-handson-focused-on-machine-learning-interpretability-h2oai

Watch the video: https://youtu.be/axIqeaUhow0


Tuesday December 5, 2017 2:02pm - 3:00pm PST
Paul Erdos Stage Computer History Museum