This article details a workflow for deploying and monitoring machine learning models. It covers using BentoML for API export and serving, Evidently for drift monitoring, and Kubeflow Notebooks with KFP for data pipeline management. The guide aims to provide a comprehensive approach to MLOps practices. AI
IMPACT Provides practical guidance on integrating MLOps tools for efficient model deployment and monitoring.
RANK_REASON The article describes the use of specific MLOps tools for model deployment and monitoring, fitting the 'tool' category.
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