Glen is an experienced professional who has used data to solve problems in many domain areas. He is currently a data scientist at NYC Data Science Academy, where he has used real-world data to solve problems. Glen worked as a scientist at the National Bioenergy Center, where he made and studied large datasets to improve biofuels and design new batteries. He was also a scientist at Argonne National Laboratory where he studied how data could be used to improve batteries and how to improve commodity chemical production. His work at these institutions resulted in a series of publications in peer-reviewed scientific journals, including invited papers and presentations.
Introduction The commute is a great equalizer. Regardless of location or income, nearly 95% of working Americans use a car or take public transit to go to and from […]
Introduction The Two-Sigma connect challenge was to predict interest-level—high, medium, or low—of RentHop apartment listings in the New York City area. This is a classification problem […]
Github In 2016, the Wall Street Journal wrote that audiobooks were the fastest growing format in publishing. As an effort to understanding this segment of the […]
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