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Data Science in 30 Minutes: Developing the FakerFact.com Fake News Detectio...

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Join The Data Incubator and Mike Tamir, Head of Data Science at Uber ATG, for the August 2018 installment of our free monthly webinar series, Data Science in 30 minutes: Developing the FakerFact Fake News Detection Algorithms.

Abstract: We will explore real world use case applications for automated “Fake News” evaluation using contemporary deep learning article vectorization and tagging. We begin with the use case and an evaluation of the appropriate context applications for various deep learning applications in fake news evaluation. We will discuss several methodologies for article vectorization with classification pipelines, ranging from traditional to advanced deep architecture techniques. We close with a discussion on troubleshooting and performance optimization when consolidating and evaluating these various techniques on active data sets.

About the speakers:

Mike Tamir

Mike Tamir serves as Head of Data Science at Uber ATG, UC Berkeley Data Science faculty, and head of Skymind Labs. He has led teams of Data Scientists in the bay area as Chief Data Scientist for InterTrust and Takt, Director of Data Sciences for MetaScale/Sears, and CSO for Galvanize where he founded the galvanizeU-UNH accredited Masters of Science in Data Science degree and oversaw the company's transformation from co-working space to Data Science organization.


Michael Li founded The Data Incubator, a New York-based training program that turns talented PhDs from academia into workplace-ready data scientists and quants. The program is free to Fellows, employers engage with the Incubator as hiring partners.

Previously, he worked as a data scientist (Foursquare), Wall Street quant (D.E. Shaw, J.P. Morgan), and a rocket scientist (NASA). He completed his PhD at Princeton as a Hertz fellow and read Part III Maths at Cambridge as a Marshall Scholar. At Foursquare, Michael discovered that his favorite part of the job was teaching and mentoring smart people about data science. He decided to build a startup to focus on what he really loves.

Michael lives in New York, where he enjoys the Opera, rock climbing, and attending geeky data science events.

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New York, NY 10003

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