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AI Infrastructure
A set of practices that combines Machine Learning DevOps and Data Engineering to deploy and maintain ML systems in production.
Detailed Explanation
MLOps (Machine Learning Operations) is a collection of practices that streamlines the development, deployment, and monitoring of machine learning models in production. It integrates principles from DevOps and Data Engineering, ensuring scalable, reliable, and efficient ML systems. MLOps emphasizes automation, versioning, testing, and continuous integration/continuous deployment (CI/CD), facilitating collaboration between data scientists and operations teams for sustainable AI deployment.
Use Cases
- •Implement automated model deployment pipeline to ensure reliable updates and monitoring of production machine learning systems.
Related Terms
Other terms in the AI Infrastructure category