Kubeflow is the machine learning toolkit for Kubernetes. It is dedicated to making deployments of machine learning workflows on Kubernetes simple, portable and scalable. The essence of Kubeflow is to provide a straightforward way to deploy open-source systems for ML to diverse infrastructures. .
Join epxerts from Mavencode and Canonical and learn how to Kubeflow is enabled on Microk8s, how to build 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 Microk8s
├── Setting up Jupyter notebook
├── Day 2
├── Kubeflow Pipelines
├── Day 3
├── Kale
├── KF serving
├── Day 4
├── Seldon core
├── TF Serving
├── Day 5
├── ML Operators
└── Katib