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.