Abstract
In this talk the speaker will discuss the recent evolution of the machine learning landscape from the perspective of the participants in the global financial industry. Several key applications of machine learning at Bloomberg will be discussed: projects such as sentiment analysis of financial news, text-based prediction of market impact, novelty detection, social media monitoring, question answering, topic clustering, and others. These interdisciplinary problems lie at the intersection of linguistics, finance, computers science and mathematics, requiring methods from signal processing, machine vision, and other fields. The speaker will talk about the methods, problem formulation, and throughout, talk practicalities of delivering machine learning solutions to real world problems in a challenging environment, highlighting issues such as appropriate problem decomposition, validation and interpretability. The speaker will also summarize the current state of the art and discuss possible future directions for the applications of machine learning in finance.
About the speaker
Mr Gary Kazantsev is the Head of the Machine Learning group at Bloomberg, leading projects at the intersection of computational linguistics, machine learning and finance, such as sentiment analysis, market impact indicators, statistical text classification, social media analytics, question answering, recommendation systems and predictive modeling of financial markets. He holds degrees in physics, mathematics and computer science from Boston University.
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