Which of the over 30 million commercial flights in the US will get actually delayed or cancelled? Freebird has built a business based on using data science to answer that question. Learn how co-founder and CTO Sam Zimmerman and his team have approached this problem by building a real-time predictive analytics engine based on dynamic data sets and Deep-Learning algorithms. This talk focuses on experiments the Freebird team has done to model the both pointwise and aggregative flight delay risk using various deep learning approaches and feature representation techniques in a risk management context.
Sam Zimmerman is software developer and data scientist with extensive experience in the commercial application of Machine-Learning algorithms. Prior to Freebird, Sam worked as a quantitative risk analyst in the currency markets and as a team lead automating a large-scale data classification problem for an energy intelligence company. Sam is a Duke grad, and works on a grant with MIT’s Computational Cognitive Science lab to extend decision theory using Machine Learning and Artificial Intelligence.