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The presentation delves into the adoption of MLOps within enterprises, examining its benefits, tools, and workflows. It discusses challenges like tool compatibility and model monitoring, proposes solutions to issues such as bias, and explores legal compliance and scalability considerations. Topics include MLOps frameworks, feature stores for streamlined operations, and designing resilient ML systems integrating CI/CD, containerization, and rollback mechanisms. Concluding with the...