1
Set Up Kubernetes Cluster
Provision a Kubernetes cluster on your preferred cloud provider or on-premises environment.
2
Install Kubeflow
Follow the official Kubeflow installation guide to deploy Kubeflow on your Kubernetes cluster using manifests or the Kubeflow Operator.
3
Access the Kubeflow Dashboard
Once installed, access the Kubeflow central dashboard to start creating and managing ML workflows.
4
Create Your First Pipeline
Use the Kubeflow Pipelines SDK to define and upload your first ML pipeline.
5
Explore Additional Components
Leverage Katib for hyperparameter tuning and KFServing for model deployment to enhance your ML lifecycle.