Build a Reproducible ML Workflow with Kubeflow Pipelines
Offered By: Linux Foundation via YouTube
Course Description
Overview
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore the process of building reproducible machine learning workflows using Kubeflow Pipelines in this informative conference talk presented by Karl Weinmeister from Google. Gain insights into leveraging Kubeflow Pipelines to create scalable and efficient ML pipelines that can be easily replicated and managed. Learn about best practices for structuring your ML projects, automating workflows, and ensuring reproducibility throughout the development lifecycle. Discover how to integrate Kubeflow Pipelines with other tools in the ML ecosystem to enhance collaboration and streamline the deployment process. Whether you're a data scientist, ML engineer, or DevOps professional, this talk offers valuable knowledge to improve your ML workflow management and reproducibility.
Syllabus
Build a Reproducible ML Workflow with Kubeflow Pipelines - Karl Weinmeister, Google
Taught by
Linux Foundation
Tags
Related Courses
Data Science BasicsA Cloud Guru Introduction to Machine Learning
A Cloud Guru Address Business Issues with Data Science
CertNexus via Coursera Advanced Clinical Data Science
University of Colorado System via Coursera Advanced Data Science Capstone
IBM via Coursera