Welcome to the first in a series of blog posts where we’ll walk you through a detailed introduction to Kubeflow. In this series, we’ll explore what Kubeflow is, how it works, and how to make it work for you. In this first blog, we’ll tackle the fundamentals, and use them as a foundation to introduce more advanced topics. Ok, let’s dive right in!

What is Kubeflow?

Kubeflow as a project got its start over at Google. The idea was to create a simpler way to run TensorFlow jobs on Kubernetes. So, Kubeflow was created as a way to run TensorFlow, based on a pipeline called TensorFlow Extended and then ultimately extended to support multiple architectures and multiple clouds so that it could be used as a framework to run entire machine learning pipelines. 

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