Presented By O’Reilly and Cloudera
Make Data Work
September 11, 2018: Training & Tutorials
September 12–13, 2018: Keynotes & Sessions
New York, NY
Patrick Hall

Patrick Hall
Principal Scientist | Senior Director, bnh.ai | H2O.ai

Website | @jpatrickhall

Patrick Hall is principle scientist at bnh.ai, a boutique law firm focused on AI and analytics; a senior director of product at H2O.ai, a leading Silicon Valley machine learning software company; and a lecturer in the Department of Decision Sciences at George Washington University, where he teaches graduate classes in data mining and machine learning.

At both bnh.ai and H2O.ai, he works to mitigate AI risks and advance the responsible practice of machine learning. Previously, Patrick held global customer-facing and R&D research roles at SAS. He holds multiple patents in automated market segmentation using clustering and deep neural networks. Patrick is the 11th person worldwide to become a Cloudera Certified Data Scientist. He studied computational chemistry at the University of Illinois before graduating from the Institute for Advanced Analytics at North Carolina State University.

Sessions

9:00am–12:30pm Tuesday, 09/11/2018
Practical techniques for interpreting machine learning models
Location: 1A 23/24 Level: Intermediate
Secondary topics:  Ethics and Privacy, Health and Medicine
Patrick Hall (bnh.ai | H2O.ai), Avni Wadhwa (H20.ai), Mark Chan (H2O.ai)
Average rating: ****.
(4.50, 4 ratings)
Transparency, auditability, and stability are crucial for business adoption and human acceptance of complex machine learning models. Patrick Hall, Avni Wadhwa, and Mark Chan share practical and productizable approaches for explaining, testing, and visualizing machine learning models using open source, Python-friendly tools such as GraphViz, H2O, and XGBoost. Read more.