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Build a Reproducible ML Workflow with Kubeflow Pipelines

Offered By: Linux Foundation via YouTube

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Kubeflow Courses Data Science Courses DevOps Courses Kubernetes Courses MLOps Courses Scalability Courses Kubeflow Pipelines Courses

Course Description

Overview

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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

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