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Overview
Machine learning and AI are rapidly transforming the world, impacting organizations of all sizes. As executives push for AI/ML strategies, DevOps teams have been upskilling and bridging the gap between operations and development for the last several years for traditional applications. The complex machine learning application arrives just as cross-team collaboration becomes familiar. These data-dependent applications present fresh challenges for deployment and development, demanding expertise from developers and data scientists, data engineers, and machine learning engineers. How can existing...
Syllabus
- Course Introduction: Welcome!
- Chapter 1: The Model Application Relationship and the Power of Reproducibility
- Chapter 2: The Model Development Lifecycle
- Chapter 3: MLOPs and the Rise of the Machine Learning Toolkit
- Chapter 4: The Origin of Kubeflow
- Chapter 5: Kubeflow Distributions
- Chapter 6: The Kubeflow Dashboard and Notebooks
- Chapter 7: The Unified Training Operator and Machine Learning
- Chapter 8: Kubeflow Pipelines
- Chapter 9: Conquering Katib
- Chapter 10: Common Kubeflow Integrations
Linux Foundation via edX
2 hours
$149.00 Certificate Available
English
On-Demand
Beginner
Instructor
Chase Christensen
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