MLOps
Machine Learning Operations: The set of practices that aims to deploy and maintain machine learning models in production reliably.
MLOps (Machine Learning Operations) is the intersection of machine learning, DevOps, and data engineering. It focuses on standardizing and streamlining the continuous delivery of high-performing AI models into production environments.
Building a model in a lab is relatively easy; deploying it to serve millions of users securely and reliably is incredibly difficult. MLOps frameworks automate the testing, deployment, and monitoring of models.
Without mature MLOps, organizations suffer from severe technical drag, as data science teams struggle to transition their experimental models into the live enterprise architecture.