Titlebook: MLOps with Ray; Best Practices and S Hien Luu,Max Pumperla,Zhe Zhang Book 2024 The Editor(s) (if applicable) and The Author(s), under exclu

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ML Observability Infrastructure,stem. The A/B testing results show a meaningful and positive impact on business metrics. However, your co-worker reminds you that your work is not yet finished. Your model needs continuous monitoring to ensure its performance remains optimal. In other words, your model is at the beginning of its operational journey.

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The Future of MLOps,h, a robust MLOps infrastructure becomes critical. Just as data infrastructure became an essential for managing and analyzing data for data-driven companies, MLOps has transformed into the essential backbone for effectively developing, deploying, managing, and monitoring AI/ML models in production at scale.

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Hien Luu,Max Pumperla,Zhe ZhangCovers up-to-date best practices and innovations in MLOps.Explains MLOps with case studies where it has been successfully adopted in organizations.Explains Ray open source project and how it might fit