Course Introduction
- Course Introduction
- Who This Course Is for
- What You Will Build in This Course
- What Is MLOps
- Problems With Traditional ML Workflows
- Kubeflow Ecosystem
Fundamentals of Kubeflow
- Kubeflow Introduction
- Benefits of Kubeflow
- Kubeflow Architecture
- Installing Kubeflow
- Demo Installing Kubeflow
- Demo What Was Installed
Working With Kubeflow
- Section Introduction
- Demo Accessing UI
- Kubeflow Pipelines
- Demo Creating Our First Pipeline
- Pipeline Parameters
- Demo Pipeline Parameters
- Customizing Component Image
- Demo Customizing Component Image
- Passing Data Between Components
- Demo Passing Data Between Components Parameters
- Demo Passing Data Between Components Artifacts
- Pipeline Control Flow
- Demo Pipeline Control Flow
- Notebooks
- Demo Section Project
KServe and Katib
- Section Introduction
- The Iris Dataset
- What Is KServe
- Installing KServe
- Deploying Iris Trained Model on KServe
- Demo Deploying Iris Trained Model on KServe
- What Is Katib
- Installing Katib
- Understanding RandomForest Regressor
- What Are Hyperparameters
- Why Update the Random Forest Program
- A Katib Experiment
- Demo Running Experiments on Katib
Profiles and Multi-Tenancy
- Section Introduction
- Authentication in Kubernetes
- Kubeflow Profiles
- Demo Adding Users in Dex
- Demo Profiles