In this webinar, we’re going to demonstrate a multi-cloud ML workflow with advanced data management on Kubeflow. We will showcase how a Data Scientist can set up their own ML development environment in minutes, start working locally, and seamlessly extend their workflow to a public cloud.

Takeaways:

  • Learn about Kubeflow, a complete ML platform on top of Kubernetes
  • Learn why data handling is critical to an end-to-end ML workflow
  • Learn how you can have all your work, along with your data, packaged, versioned and reproducible across every step of your ML workflow
  • Learn how you can run ML workflows that span hybrid and multi-cloud environments