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The Evolution of DevOps in Data Science
This chapter explores the integration of DevOps within the data science realm, highlighting its contrast with MLOps and discussing the historical progression from traditional methodologies to agile practices. It emphasizes the challenges of transitioning data science projects into production, the importance of interpersonal relationships, and the broader responsibilities of data scientists beyond model building. The chapter concludes with information about a related book and personal insights from the hosts.