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Toward an Open Source MLOps Architecture
DOI:10.1109/MS.2024.3421675.png)
Abstract
En 中文
We present a Kubernetes-based, open source MLOps framework to streamline the lifecycle management of machine learning models in production environments. We compared state-of-the-art MLOps tools and frameworks, demonstrating that ours meets the same features as proprietary options, such as Amazon SageMaker.
Keywords:
Pipelines
Computer architecture
Monitoring
Production
Testing
Python
Predictive models

