Getting Started with Kubeflow
Chase Christensen:
Overview
Explore the origins, deployment options, individual components and common integrations of Kubeflow. By the end of this course, you will understand Kubeflow’s architecture and key components with some hands on examples This course is designed for developers, engineers, data scientists or anyone interested in understanding the anatomy of a machine learning tool kit that harnesses the power of Kubernetes.
LABS
Content from the Linux Foundation program, “Introduction to AI/ML Toolkits with Kubeflow (LFS147),” will be closely followed by Chase who is the author of this training program. Students should watch their email for instructions on how to setup a Google Cloud account for use with these labs.
STUDENT REQUIREMENTS AND PREREQUISITES
Participants should have a System Administration / Linux background with the following suggested tools and/or skills:
- Competency on the Linux® command line
- A general/high-level understanding of Linux containers(e.g., Docker, CRI-O, etc.)
- A general/high-level understanding of authentication(e.g., LDAP/AD)
- A laptop computer running Windows, macOS, or Linux with the Firefox or Chrome web browser
WHAT STUDENTS SHOULD BRING
A laptop with internet access and ssh access to a public address. A VM or laptop with a Linux environment if students want to do things locally.
Instructor’s Bio
Chase Christensen is a people-prioritized solutions engineer with a passion for open-source technology and enabling teams to solve complex problems. At TileDB, he bridges the gap between human interaction and innovative data solutions, helping teams harness the power of machine learning and multi-modal applications.
Date and Time
Sunday, December 15, 2024
- Morning session: 9:00 AM to 12:30 PM
- Lunch break: 12:30 to 1:30 PM
- Afternoon session: 1:30 PM to 5:00 PM
Registration
Go to the registration page to register for the training course. When you register you will be able to choose a bundle with one or multiple classes.