MLOps: Definition, Importance, and Implementation

MLOps, or Machine Learning Operations, is a set of techniques and tools for deploying models in production environments. Lately, the effectiveness of DevOps in reducing the time between software updates and eliminating gaps has been crucial to the existence of any business.

Machine learning professionals turned to the machine learning sector to implement the DevOps principle, creating MLOps. Integrating the CI/CD principle with the machine learning model enables the data world to integrate and deliver production-ready models promptly. In addition, MLOps introduce new Continuous Training (CT) and Continuous Monitoring (CM) principles, making the production environment even more suitable for any machine learning model.

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