Presented By O'Reilly and Cloudera
Make Data Work
Dec 4–5, 2017: Training
Dec 5–7, 2017: Tutorials & Conference
Singapore
Graham Williams

Graham Williams
Director, Data Science, Microsoft

Website

Graham Williams is director of data science at Microsoft, where he is responsible for the Asia-Pacific region, an adjunct professor with the University of Canberra and the Australian National University, and an international visiting professor with the Chinese Academy of Sciences. Graham has 30 years’ experience as a data scientist leading research and deployments in artificial intelligence, machine learning, data mining, and analytics. Previously, he was principal data scientist with the Australian Taxation Office and lead data scientist with the Australian Government’s Centre of Excellence in Analytics, where he assisted numerous government departments and Australian industry in creating and building data science capabilities. He has also worked on many projects focused on delivering solutions and applications driven by data using machine learning and artificial intelligence technologies. Graham has authored a number of books introducing data mining and machine learning using the R statistical software.

Sessions

5:05pm5:45pm Thursday, December 7, 2017
Le Zhang (Microsoft), Graham Williams (Microsoft)
Average rating: ***..
(3.00, 1 rating)
R has long been criticized for its limitations on scalable data analytics. What's needed is an R-centric paradigm that enables data scientists to elastically harness cloud resources of manifold computing capability for large-scale data analytics. Le Zhang and Graham Williams demonstrate how to operationalize an E2E enterprise-grade pipeline for big data analytics—all within R. Read more.