For those interested in a fully managed solution, Amazon Web Services recently announced Amazon SageMaker Pipelines at re:Invent 2020, the first purpose-built, easy-to-use continuous integration and continuous delivery (CI/CD) service for machine learning (ML). In this post, we’ll show how the open-source platform MLflow helps address these issues. During the operational phase, you also need to manage the different model versions going to production and your lifecycle. With the rapid adoption of machine learning (ML) and MLOps, enterprises want to increase the velocity of ML projects from experimentation to production.ĭuring the initial phase of an ML project, data scientists collaborate and share experiment results in order to find a solution to a business need.
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