What accounts for flight delays in the U.S.? This project portrays the machine learning end of a large data engineering project that merged 630 million rows of weather data against 31 million rows of flight data. I use the state-of-the-art in distributed deep learning by leveraging Petastorm, Horovod, and PyTorch to produce a multilayer perceptron model that is distributed across 8 workers in DataBricks. Importantly, I use novel approaches to transform categorical data into continuous features through an embedding table. To view this project, please click here.