Using Kubeflow Pipelines for Building Machine Learning Pipelines
Kubeflow is an open-source project dedicated to making deployments of machine learning workflows on Kubernetes simple, portable and scalable. This session will focus on Kubeflow Pipelines, a platform …
| Talk Title | Using Kubeflow Pipelines for Building Machine Learning Pipelines |
| Speakers | Yufeng Guo (Developer Advocate, Machine Learning, Google) |
| Conference | Open Source Summit + ELC Europe |
| Conf Tag | |
| Location | Lyon, France |
| Date | Oct 27-Nov 1, 2019 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
Kubeflow is an open-source project dedicated to making deployments of machine learning workflows on Kubernetes simple, portable and scalable. This session will focus on Kubeflow Pipelines, a platform to enable end-to-end orchestration of ML pipelines as well as easy experimentation and re-use. You’ll learn how to build and manage machine learning workloads that can scale.Kubeflow is a very exciting open-source project that bridges the gap between the DevOps world with the machine learning world. There are many concepts that can be highly valuable to cross-pollinate between these worlds, and Kubeflow helps codify that into best practices.Learn more about Kubeflow Pipelines at https://www.kubeflow.org/docs/pipelines/pipelines-overview/
