Speaker "Rumman Chowdhury" Details Back



3-hour Applied Tensorflow tutorial


This tutorial will spend the first hour covering the basics of tensorflow, then show specific implementations.


Rumman comes to data science from a quantitative social science background. Prior to joining Metis, she was a data scientist at Quotient Technology, where she used retailer transaction data to build an award-winning media targeting model. Her industry experience ranges from public policy, to economics, and consulting. Her prior clients include the World Bank, the Vera Institute of Justice, and the Los Angeles County Museum of the Arts. She holds two undergraduate degrees from MIT, a Masters in Quantitative Methods of the Social Sciences from Columbia, and she is currently finishing her Political Science PhD from the University of California, San Diego. Her dissertation uses machine learning techniques to determine whether single-industry towns have a broken political process. Her passion lies in teaching and learning from teaching.