Presented By O’Reilly and Cloudera
Make Data Work
March 5–6, 2018: Training
March 6–8, 2018: Tutorials & Conference
San Jose, CA
Goodman Gu

Goodman Gu
Head of Machine Learning Architecture, Cogito

Website | @goodman_gu

Goodman Xiaoyuan Gu is head of machine learning architecture at Boston-based Cogito, where he leads operations of large-scale real-time augmented intelligence platform. Previously, he headed marketing data engineering at Atlassian and was vice president of technology at CPXi, director of engineering at Dell, and general manager at Amazon, where he built marketing, analytics and machine learning applications. He has served on technical program committees of two IEEE flagship conferences and is the author of over a dozen academic publications in high-profile IEEE and ACM journals and conferences. Goodman holds a degree in engineering and management from MIT.

Sessions

4:20pm–5:00pm Thursday, March 8, 2018
Not your parents' machine learning: How to ship an XGBoost churn prediction app in under four weeks
Big data and data science in the cloud, Data science and machine learning
 Location: LL20 D
Goodman Gu (Cogito)
Average rating: *****
(5.00, 3 ratings)
Machine learning is a pivotal technology. However, bringing an ML application to life often requires overcoming bottlenecks not just in the model code but in operationalizing the end-to-end system itself. Goodman Gu shares a case study from a leading SaaS company that quickly and easily built, trained, optimized, and deployed an XGBoost churn prediction ML app at scale with Amazon SageMaker. Read more.