Presented By O'Reilly and Cloudera
Make Data Work
September 25–26, 2017: Training
September 26–28, 2017: Tutorials & Conference
New York, NY
David Talby

David Talby
Chief Technology Officer, Pacific AI

Website | @davidtalby

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 was with Microsoft’s Bing group, where he led business operations for Bing Shopping in the US and Europe, and at Amazon, where he built and ran distributed teams that helped scale Amazon’s financial systems. David holds a PhD in computer science and master’s degrees in both computer science and business administration.

Sessions

1:30pm5:00pm Tuesday, September 26, 2017
Data science & advanced analytics, Machine Learning & Data Science
Location: 1A 23/24 Level: Intermediate
Secondary topics:  Deep learning, Pydata, Text
David Talby (Pacific AI), Claudiu Branzan (Accenture), Alex Thomas (John Snow Labs)
Natural language processing is a key component in many data science systems that must understand or reason about text. David Talby, Claudiu Branzan, and Alex Thomas lead a hands-on tutorial on scalable NLP using spaCy for building annotation pipelines, TensorFlow for training custom machine-learned annotators, and Spark ML and TensorFlow for using deep learning to build and apply word embeddings. Read more.
1:15pm1:55pm Wednesday, September 27, 2017
Location: O'Reilly booth (Table A)
David Talby (Pacific AI)
Got questions on applying machine learning, natural language processing, and deep learning, especially in the domains of healthcare and life sciences? Stop by and meet David. Read more.
5:25pm6:05pm Wednesday, September 27, 2017
Data science & advanced analytics, Machine Learning & Data Science
Location: 1A 06/07 Level: Intermediate
David Talby (Pacific AI)
Average rating: *****
(5.00, 2 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.