How ADP Uses Machine Learning to Get Better Insights from HR & Payroll Data

This was meetup presented to the NYC Big Data Science meetup group on June 27, 2017.
Xiaojing Wang is Automatic Data Processing’s (ADP’s) Analytics Principal Data Scientist and Senior Director of Data Science group, responsible for ADPBenchmarks and related data product and platform development. She leads a team of data scientists and engineers that build machine learning and big data platform and deliver data products combining ADP’s rich HCM data with cutting edge technologies in Big Data, machine learning, and predictive analytics. Prior to joining ADP, Xiaojing was Principal Consultant for Intelogic, advising clients ranging from startups to established financial companies on data product strategies and data architecture. Xiaojing also spent 10 years in CNET, building its enterprise data warehouse, business intelligence infrastructure and big data-driven advertising delivery engine optimization. She created the first revenue generating data product and led the development of first terabyte advertising data mart enabling advanced ad delivery and optimization.
Xiaojing earned her Bachelor’s degree in Computer Science and Engineering from University of Science and Technology of China and her Master’s in Computer Science from The University of South Carolina at Columbia.
Abstract:
Graphics processing units (GPUs) are becoming integral components of modern machine learning engines and platforms. This meetup will provide an introduction to GPUs and their suitability for machine learning workloads. We will also discuss enabling technologies, such as CUDA, and demonstrate GPU-accelerated machine learning with the H2O platform. This talk is targeted to machine learning practitioners new to GPUs.