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What is MLOps?

 

MLOps, short for "Machine Learning Operations," is a set of practices and tools that enable organizations to effectively develop, deploy, and manage machine learning (ML) models at scale. MLOps combines the principles and practices of DevOps, Agile software development, and data engineering with ML-specific tools and technologies.

MLOps involves automating and streamlining the entire machine learning lifecycle, from data preparation and model training to model deployment and monitoring. This includes version control, continuous integration and deployment, automated testing, model packaging, and model serving. By implementing MLOps, organizations can improve the efficiency, reliability, and scalability of their machine learning initiatives, as well as enhance the quality and performance of their models.