This guide walks through setting up a local Kubernetes cluster, installing Kubeflow, and running an end-to-end ML pipeline (training and serving) with Kubeflow Pipelines and KServe. We’ll use a scikit-learn model example and show commands and sample outputs at each step. All commands are run on a Linux or macOS terminal unless noted otherwise.
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