Sep 23–26, 2019

Felix Cheung
Sr Engineering Manager, Uber

Felix Cheung is a senior engineering manager at Uber and a PMC and committer for Apache Spark. Felix started his journey in the big data space about five years ago with the then-state-of-the-art MapReduce. Since then, he’s (re-)built Hadoop clusters from metal more times than he would like, created a Hadoop distro from two dozen or so projects, and juggled hundreds to thousands of cores in the cloud or in data centers. He built a few interesting apps with Apache Spark and ended up contributing to the project. In addition to building stuff, he frequently presents at conferences, meetups, and workshops. He was also a teaching assistant for the first set of edX MOOCs on Apache Spark.

Sessions

11:20am–12:00pm Wednesday, September 25, 2019

Location: 1A 08/10

We run, we improve, we scale: The XGBoost story at Uber

Data Science, Machine Learning, & AI

Secondary topics: Deep dive into specific tools, platforms, or frameworks, Transportation and Logistics

Nan Zhu (Uber), Felix Cheung (Uber)

XGBoost has been widely deployed in companies across the industry. Nan Zhu and Felix Cheung dive into the internals of distributed training in XGBoost and demonstrate how XGBoost resolves the business problem in Uber with a scale to thousands of workers and tens of TB of training data. Read more.