Machine Learning Operations (MLOps) for Generative AI

MLOps (Machine Learning Operations) represents the intersection of machine learning and DevOps practices, aimed at automating the deployment, monitoring, and management of machine learning models in production environments. This paper explores the various levels of MLOps automation, compares the methodologies of custom ML and AutoML, and presents a case study on the implementation of MLOps for fraud detection. We also discuss the advantages, limitations, and real-world applications of these methodologies in various domains. Through this analysis, we aim to provide insights into optimizing machine learning workflows and enhancing model deployment processes.