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October 13 - 15


Machine Learning

2-for-1: Deploy your ML Workloads on Kubernetes with Kubeflow/How do you get Started Doing AI?

Karl Weinmeister    Gordon Haff   

Karl Weinmeister – Deploy your ML Workloads on Kubernetes with Kubeflow (Introductory)

Kubeflow is an open-source project dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable. In this talk, you’ll learn about the problems Kubeflow solves and how it works.

We will cover:

  • How end-to-end ML workflows require heavy lifting from DevOps
  • What are typical problems that Kubeflow solves
  • What are the main components of Kubeflow
  • How does Kubeflow interact with Kubernetes

Gordon Haff – How do you get Started Doing AI? (Introductory)

With all the market interest in artificial intelligence, it’s no surprise that many are asking about the best way to learn more about it. What should I read? What should I watch? There’s so much material out there. But, before one can properly answer those types of questions, it’s useful to take a step back and consider what “doing AI” even means because it turns out that AI can mean a lot of different things depending upon what you’re trying to accomplish.

In this talk, Gordon Haff will provide you with both a high-level roadmap and specific pointers for adding AI smarts to your toolbox. He’ll distinguish between research AI and applied AI, discuss how AI intersects with data science more broadly, and look at some of related research and practice areas that will help you understand AI beyond just machine learning. Armed with this knowledge, you will be better prepared to chart out a program for learning AI that targets your specific needs and objectives rather than wasting time on topics that are not interesting or relevant to you.