Build Scalable and Modular Learning Systems: Machine learning and data-driven approaches are becoming very important in many areas. There are one factors that drive these successful applications: scalable learning systems that learn the model of interest from large datasets. More importantly, the system needed to be designed in a modular way to work with existing ecosystem and improve users’ productivity environment. In this talk, I will talk about XGBoost and MXNet, two learning scalable and portable systems that I build. I will discuss how we can apply distributed computing, asynchronous scheduling and hardware acceleration to improve these systems, as well as how do they fit into bigger open-source ecosystem of machine learning.