Introduction to Kubeflow
In this episode, Michael will introduce us to Kubeflow's new features, shipping in Kubeflow 1.3, and guide us through everything we need to get started running our data science workloads on Kubernetes with Kubeflow.🍿 Rawkode LiveHosted by David McKay / 🐦 https://twitter.com/rawkodeWebsite: https://rawkode.liveDiscord Chat: https://rawkode.live/chat#RawkodeLive🕰 Timeline00:00 - Holding screen00:40 - Introductions06:00 - What is Kubeflow?42:00 - Introduction to Machine Learning by Example59:00 - Working with Kubeflow Notebooks1:54:00 - Deploying with Kale👥 About the Guests Michael Tanenbaum Solutions Engineer @arrikto🐦 https://twitter.com/tbaums🧩 https://github.com/tbaums🔨 About the TechnologiesKubeflowThe Kubeflow project is dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable. Our goal is not to recreate other services, but to provide a straightforward way to deploy best-of-breed open-source systems for ML to diverse infrastructures. Anywhere you are running Kubernetes, you should be able to run Kubeflow.🌏 https://www.kubeflow.org/🐦 https://twitter.com/kubeflow🧩 https://github.com/kubeflow/kubeflow#Deep Learning #Machine Learning #Data Science