MLOps for DevOps People
DevOps and Docker Talk: Cloud Native Interviews and Tooling
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Navigating the MLOps Landscape
This chapter explores the evolving roles of ML engineers and data scientists within the machine learning ecosystem, emphasizing how MLOps streamline these roles through self-service frameworks. It discusses the complexities faced by DevOps engineers when managing machine learning workloads, highlighting the need for specialized tools and observability measures. The chapter also addresses the transition from traditional DevOps to MLOps, emphasizing the importance of collaboration, security considerations, and understanding data science processes.
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