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

Paco Nathan
Evil Mad Scientist, derwen.ai

Website | @pacoid

Paco Nathan is known as a “player/coach” with core expertise in data science, natural language processing, machine learning, and cloud computing. He has 35+ years of experience in the tech industry, at companies ranging from Bell Labs to early-stage startups. His recent roles include director of the Learning Group at O’Reilly and director of community evangelism at Databricks and Apache Spark. Paco is the cochair of Rev conference and an advisor for Amplify Partners, Deep Learning Analytics, Recognai, and Primer. He was named one of the "top 30 people in big data and analytics" in 2015 by Innovation Enterprise.

Sessions

9:00am–9:05am Tuesday, 09/11/2018
Data Case Studies welcome
Location: 1E 10
Paco Nathan (derwen.ai)
Program chair Alistair Croll welcomes you to the Data Case Studies tutorial. Read more.
3:30pm–4:10pm Thursday, 09/13/2018
Executive Briefing: Best practices for human in the loop—The business case for active learning
Location: 1E 14 Level: Non-technical
Paco Nathan (derwen.ai)
Average rating: ***..
(3.00, 1 rating)
Deep learning works well when you have large labeled datasets, but not every team has those assets. Paco Nathan offers an overview of active learning, an ML variant that incorporates human-in-the-loop computing. Active learning focuses input from human experts, leveraging intelligence already in the system, and provides systematic ways to explore and exploit uncertainty in your data. Read more.