Presented By O'Reilly and Cloudera
Make Data Work
March 13–14, 2017: Training
March 14–16, 2017: Tutorials & Conference
San Jose, CA
Feng Zhu

Feng Zhu
Lead Machine Learning Scientist, Clobotics

| Attendee Directory Profile

Feng Zhu is a machine learning scientist at Clobotics. He is leading a team of engineers and scientists to build computer vision recognition platform for FMCG (fast-moving consumer goods) retailers and manufacturers. Previously, Feng Zhu was a senior data scientist at C+E Analytics and Insights within Microsoft, where he focused on building end-to-end solutions for various problems in the Microsoft Cloud business using advanced machine learning techniques. Before joining Microsoft, Feng was a research scientist on the Fraud Detection and Risk Management team at Amazon, where he collaborated with various business and engineering teams to provide fraud detection and mitigation solutions for the Pay with Amazon product. He holds a PhD in electrical engineering and MS degrees in electrical engineering and applied mathematics from the University of Notre Dame and a BS from Harbin Institute of Technology, China.

Sessions

11:00am11:40am Wednesday, March 15, 2017
Data science & advanced analytics
Location: 210 C/G Level: Intermediate
Secondary topics:  Deep learning, ecommerce, Retail
Feng Zhu (Clobotics), Valentine Fontama (Microsoft)
Average rating: ****.
(4.71, 7 ratings)
Although deep learning has proved to be very powerful, few results are reported on its application to business-focused problems. Feng Zhu and Val Fontama explore how Microsoft built a deep learning-based churn predictive model and demonstrate how to explain the predictions using LIME—a novel algorithm published in KDD 2016—to make the black box models more transparent and accessible. Read more.