January 2, 2020

145 words 1 min read

Build, train, and deploy ML with Kubeflow: Using AI to label GitHub issues

Build, train, and deploy ML with Kubeflow: Using AI to label GitHub issues

Turning ML into magical products often requires complex distributed systems that bring with them a unique ML-specific set of infrastructure problems. Using AI to label GitHub issues as an example, Jeremy Lewi and Hamel Husain demonstrate how to use Kubeflow and Kubernetes to build and deploy ML products.

Talk Title Build, train, and deploy ML with Kubeflow: Using AI to label GitHub issues
Speakers Jeremy Lewi (Google), Hamel Husain (GitHub)
Conference O’Reilly Artificial Intelligence Conference
Conf Tag Put AI to Work
Location New York, New York
Date April 16-18, 2019
URL Talk Page
Slides Talk Slides
Video

Turning ML into magical products often requires complex distributed systems that bring with them a unique ML-specific set of infrastructure problems. Using AI to label GitHub issues as an example, Jeremy Lewi and Hamel Husain demonstrate how to use Kubeflow and Kubernetes to build and deploy ML products.

comments powered by Disqus