Machine Learning at Bloomberg

In this talk Gary Kazantsev from the R&D Machine Learning group at Bloomberg will speak about current projects involving Machine Learning and applications such as Natural Language Processing. We will discuss the evolution and development of several key Bloomberg projects such as sentiment analysis, market impact prediction, novelty detection, social media monitoring, information extraction, recommendation systems and question answering. We will show that these interdisciplinary problems lie at the intersection of linguistics, finance, computer science and mathematics, requiring methods from signal processing, machine vision and other fields. Throughout, we will talk about practicalities of delivering machine learning solutions to problems of finance and highlight issues such as importance of appropriate problem decomposition, feature engineering and interpretability.

There will be a discussion of future directions and applications of Machine Learning in finance as well as a Q&A session.