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In this series of posts, we will take a small dataset and go through various steps like building Data pipelines, ML workflow management, API development and Monitoring. These steps are necessary for operationalization of any machine-learning based model. These posts are in no way exhaustive in covering the breadth of MLOps.Several key pieces like the CI/CD pipeline, monitoring for drift, etc are missing at the moment, which might get added later. Stack We will be using the followin...