From the course: Leveraging Cloud-Based Machine Learning on Google Cloud Platform: Real World Applications

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Kubeflow overview

Kubeflow overview - Google Cloud Tutorial

From the course: Leveraging Cloud-Based Machine Learning on Google Cloud Platform: Real World Applications

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Kubeflow overview

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- [Narrator] So what is Kubeflow and why are we talking about it here in the context of machine learning on Google Cloud Platform? Well, those of you who leverage Kubernetes or basically a container-orchestration engine, that runs pretty much on all public clouds, understand the importance of that platform. Kubeflow is about deploying machine learning workflows on Kubernetes and making it useful. In other words, binding it to Kubernetes in container-based application. So it's applicable anywhere where Kubernetes runs. Kubernetes is an open-source project, so it runs everywhere. Kubeflow is also open-source and runs everywhere. Anywhere Kubernetes runs. And it provides a way to deploy open-source systems to machine learning and very heterogeneous infrastructures. So keep in mind that Kubeflow is important because Kubernetes is important. And that a bound Kubernetes and the ability to, in essence, build machine learning…

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