Named-Entity Recognition and the spaCy Library

Topic:

Named-Entity Recognition (NER) is highly useful for information retrieval tasks such as question answering. At the same time, it is a difficult problem. This talk has three objectives:

1. provide an overview of approaches for the NER task
2. discuss the spaCy package for NLP, which includes NER
3. present a use case from Carpe Data, a Santa Barbara insurtech startup

About the Speaker:

Adam Tashman, PhD
VP, Head of Data Science at Carpe Data
Visiting Associate Professor, UCSB Department of Statistics and Probability

Adam has over fifteen years of experience in quantitative finance and machine learning, where his work has spanned research, analytics, risk, portfolio management, model development, and model validation. He has worked at a broad range of firms including hedge funds, investment banks, and commercial banks. His roles include Head of Analytics at a Boston-based startup financial technology company, and Vice President of Quantitative Research at Citigroup in their Global Managed Investments department. Adam holds a BA in Mathematics from the University of Virginia, an MA from Columbia University in Mathematical Finance, and an MS and PhD from Stony Brook University in Applied Mathematics and Statistics.

We will have Pizza and Drinks at the event for the participants.