Presented By O’Reilly and Intel AI
Put AI to work
Sep 4-5, 2018: Training
Sep 5-7, 2018: Tutorials & Conference
San Francisco, CA
Jian Wu

Jian Wu
Full Stack Engineer, NIO

Website

Jian Wu is a full stack engineer at NIO US. Before joining NIO, he was a data analytics developer at Samsung SDSRA’s AI and Machine Learning Lab working on machine learning projects using Kubernetes, Python, and TensorFlow, he also developed Web UI and Dashboard using JavaScript with AngularJS, D3.js, and Bootstrap. Jian has been a software developer in the San Francisco Bay Area for 20+ years, he developed a device gateway and a REST-style WS server when working at Netflix, developed a payment gateway when working at eBay/PayPal, and worked at Oracle for 8+ years developing Java middle-tier server and applications.

Sessions

2:35pm-3:15pm Thursday, September 6, 2018
Evaluate deep Q-learning for sequential targeted marketing with 10-fold cross-validation
Implementing AI
 Location: Continental 1-3
Secondary topics:  Reinforcement Learning, Temporal data and time-series
Jian Wu (NIO)
Jian Wu discusses an end-to-end engineering project to train and evaluate deep Q-learning models for targeting sequential marketing campaigns using the 10-fold cross-validation method. Jian also explains how to evaluate trained DQN models with neural network-based baseline models and shows that trained deep Q-learning models generally produce better-optimized long-term rewards. Read more.