Kubeflow is the open source machine learning toolkit on top of Kubernetes.
Kubernetes is the industry standard for software delivery at scale and Kubeflow provides the cloud-native interface between K8s and data science tools - libraries, frameworks, pipelines, notebooks - bringing the Ops to ML.
This repo is part of the 5-day Kubeflow enterprise training provided by Canonical and Mavencode.
Throughout this training, experts from Mavencode and Canonical will guide you through the steps from installing Kubeflow to building real-world machine learning pipelines using Kubeflow & Kale, serve your models, how ML operators and TF jobs work and how to tune model parameters with Katib.
├── Day 1
├── Setting up Kubeflow on Microk8s
├── Setting up Jupyter notebooks on Kubeflow
├── Day 2
├── Kubeflow Pipelines
├── Day 3
├── Kale
├── KF serving
├── Day 4
├── Seldon Core
├── TF Serving
├── Day 5
├── ML Operators
└── Katib