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

Kubernetes plays Cupid for data scientists and IT (sponsored by MapR)

Skyler Thomas (MapR)
1:15pm–1:55pm Wednesday, 09/12/2018
Location: 1A 01/02
Average rating: *****
(5.00, 2 ratings)

What you'll learn

  • Learn how Kubernetes helps data scientists and IT work in concert to speed model training and time-to-value


In the past, there have been major challenges in quickly creating machine learning training environments and deploying trained models into production. Skyler Thomas describes some of the challenges that data scientists and IT face as they work together to infuse AI and ML into their organization, focusing on how the right technologies, including Kubernetes, can help you overcome these challenges and get the best models to production quickly.

You’ll learn how to use TensorFlow, MapR, and other tools to train different ML models against a publicly available dataset and discover how to move those models to production quickly, with minimal friction between data scientists and IT, and implement production A/B testing to select the right model. Skyler concludes by connecting the dots to other real-world ML use cases that would benefit from this approach in an increasingly hybrid cloud world.

This session is sponsored by MapR.

Skyler Thomas


Skyler Thomas is an engineer at MapR, where he is designing Kubernetes-based infrastructure to deliver machine learning and big data applications at scale. Previously, Skyler was chief architect for WebSphere user experience at IBM, where he worked with more than a hundred customers to deliver extreme-scaled applications in the healthcare, financial services, and retail industries.