Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA
David Talby

David Talby
Chief Technology Officer, Pacific AI

Website | @davidtalby

David Talby is a chief technology officer at Pacific AI, helping fast-growing companies apply big data and data science techniques to solve real-world problems in healthcare, life science, and related fields. David has extensive experience in building and operating web-scale data science and business platforms, as well as building world-class, agile, distributed teams. Previously, he led business operations for Bing Shopping in the US and Europe with Microsoft’s Bing Group and built and ran distributed teams that helped scale Amazon’s financial systems with Amazon in both Seattle and the UK. David holds a PhD in computer science and master’s degrees in both computer science and business administration.

Sessions

9:00am–12:30pm Tuesday, March 26, 2019
Natural language understanding at scale with Spark NLP
Data Science, Machine Learning & AI
 Location: 2009
Secondary topics:  Deep Learning, Text and Language processing and analysis
David Talby (Pacific AI), Alex Thomas (John Snow Labs), Claudiu Branzan (Accenture)
Average rating: ****.
(4.75, 8 ratings)
David Talby, Alex Thomas, and Claudiu Branzan lead a hands-on introduction to scalable NLP using the highly performant, highly scalable open source Spark NLP library. You’ll spend about half your time coding as you work through four sections, each with an end-to-end working codebase that you can change and improve. Read more.
11:50am–12:30pm Thursday, March 28, 2019
Executive Briefing: Why machine-learned models crash and burn in production and what to do about it
Executive Briefing and best practices, Strata Business Summit
 Location: 2020
Secondary topics:  Model lifecycle management
David Talby (Pacific AI)
Average rating: ****.
(4.90, 10 ratings)
Machine learning and data science systems often fail in production in unexpected ways. David Talby shares real-world case studies showing why this happens and explains what you can do about it, covering best practices and lessons learned from a decade of experience building and operating such systems at Fortune 500 companies across several industries. Read more.