In this talk, Terry will present an overview of neural networks and several applications that he has developed over the years. That is, he begins by describing artificial neurons, their activation functions, and error back propagation. This is followed by a discussion of why neural networks work, and a description of early applications of neural networks for detecting fraudulent credit card transactions and predicting which clients will give up their credit cards. He next describes several methods for interpreting neural network decisions (i.e., demystifying the “black box”). This is followed by applications in bond trading including networks used to trade US Treasury bonds, predicting market moves from investor trading patterns, and predicting corporate bond spread moves. Finally, he discusses using sentiment data to predict corporate bond market moves and conclude with a brief discussion of how artificial intelligence/machine learning is transforming bond markets.
Niki Athanasiadou is the principal data scientist in Common Sense Analytics LLC, and a data scientist in the Mountain View-based H2O.ai, working closely with companies in the healthcare industry and beyond helping them to expand their capabilities using AI. Having earned a PhD in molecular and cellular biology by the University of Edinburgh (UK), her past experience includes computational modeling in genomic research, medicine, and population health. As a fellow in the NIH (US), Niki prototyped a pipeline that uses genomic and EHR-level information to create personalized models of disease risk. Alongside being published in international peer-reviewed journals, Niki's work has earned several awards in the UK and US, including the NYC Open Data competition for a Data Science project in 2018.
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