Presented By O’Reilly and Cloudera
Make Data Work
21–22 May 2018: Training
22–24 May 2018: Tutorials & Conference
London, UK
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

13:30–17:00 Tuesday, 22 May 2018
Natural language understanding at scale with spaCy and Spark NLP
Data science and machine learning
 Location: Capital Suite 13 Level: Intermediate
Secondary topics:  Text and Language processing and analysis
David Talby (Pacific AI), Claudiu Branzan (Accenture)
Average rating: ****.
(4.33, 3 ratings)
Natural language processing is a key component in many data science systems. David Talby and Claudiu Branzan lead a hands-on tutorial on scalable NLP using spaCy for building annotation pipelines, Spark NLP for building distributed natural language machine-learned pipelines, and Spark ML and TensorFlow for using deep learning to build and apply word embeddings. Read more.
17:25–18:05 Wednesday, 23 May 2018
Executive Briefing: Why machine-learned models crash and burn in production and what to do about it
Data-driven business management, Executive Briefing, Strata Business Summit
 Location: Capital Suite 17 Level: Intermediate
Secondary topics:  Managing and Deploying Machine Learning
David Talby (Pacific AI)
Average rating: ****.
(4.00, 1 rating)
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.
14:05–14:45 Thursday, 24 May 2018
Spark NLP in action: Intelligent, high-accuracy fact extraction from long financial documents
Data science and machine learning, Expo Hall
 Location: Expo Hall Level: Intermediate
Secondary topics:  Financial Services, Text and Language processing and analysis
David Talby (Pacific AI), Saif Addin Ellafi (John Snow Labs), Paul Parau (UiPath)
Average rating: ****.
(4.50, 4 ratings)
Spark NLP natively extends Spark ML to provide natural language understanding capabilities with performance and scale that was not possible to date. David Talby, Saif Addin Ellafi, and Paul Parau explain how Spark NLP was used to augment the Recognos smart data extraction platform in order to automatically infer fuzzy, implied, and complex facts from long financial documents. Read more.