Thanks for your interest in this Dataiku NYC Meetup! The health & safety of our attendees & speakers is our primary concern. While this currently proves to be a tricky time for public gatherings, Dataiku is still committed to providing great tech content & facilitating discussions in the data science space. As such, weve decided to pivot towards online webinars via our partner platform, BrightTalk.|
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Tentative Schedule: (ET)
4:05pm: Exploring Marketing Disparities Using Neural Nets
Point of sale tobacco (POST) advertising is an embedded element of the urban landscape of New York City. It's comprised of a variety of marketing practices including signs on the insides & outsides of retail stores & has a more immediate & comprehensive effect on tobacco sales than any other marketing channel. There is substantial evidence of disparity in the way tobacco products are advertised at the point of sale depending on the community demographic profile of focus. The goal of this project is to map POST marketing practices across New York City (NYC) using an automated method of detecting & classifying tobacco signage. In comparing the POST landscape with socioeconomic characteristics at the neighborhood level, the work also aims to explore marketing disparities & variable exposure of communities to tobacco advertisements. In this project, the state-of-the-art convolutional neural network, Faster R-CNN model has been used to identify signs & discriminate tobacco signages from other types of signs in NYC.
Isha is a principal data scientist at Capital One. Prior to that, she worked at Ericsson as a data scientist. She completed her master's from New York University from an Urban Data Science program in 2018. She moved to the Bay Area in 2018 & before, worked in different NYU research labs (NYU Urban Observatory, NYU Audio Lab, etc.). Before moving to New York, Isha lived in Hong Kong for 5 years, where she did her bachelors from Hong Kong University of Science & Tech (HKUST) in Environmental Technology & Computer Science & later worked in HKUST- Deutsche Telecom Systems & Media lab (an Augmented Reality & Computer Vision focused lab) as a Research Assistant.
Disclaimer: All views, thoughts, & opinions expressed in the webinar belong solely to the panelists, & not to the panelists employer, organization, committee, other group or individual.