Sep 23–26, 2019

Nan Zhu
Software Engineer, Uber

Nan Zhu is a software engineer at Uber. He works on optimizing Spark for Uber’s scenarios and scaling XGBoost in Uber’s machine learning platform. Nan has been the committee member of XGBoost since 2016. He started the XGBoost4J-Spark project facilitating distributed training in XGBoost and fast histogram algorithms in distributed training.

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.