Often referred to as MLOps, machine learning operations applies DevOps software development principles and methodologies to a machine learning algorithm’s lifecycle. Developers use the process to increase an algorithm’s effectiveness and value over time through ongoing post-launch support.
MLOps is an iterative approach that can simplify production quality and scale. Also, developers use MLOps to automate development tasks. MLOps embraces multiple DevOps practices, including Continuous Integration and Continuous Deployment (CI/CD).
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