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Delivering Production-Grade Machine Learning Outcomes with MLOps

With machine learning (ML) models taking an average of ninety days or longer to deploy, enterprises are exploring MLOps to improve deployment speed, reliability, and success rates.

What Is MLOps?

Just as DevOps linked software development with operations, MLOps links two disparate areas of machine learning: development of the machine learning model and operating it in production. Linking these areas requires the right team, and automated processes around continuous integration and deployment, bringing in aspects of DevOps. MLOps also requires broad collaboration between data scientists, infrastructure experts and data engineers.

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