In this episode, we will explore Uber’s Model Excellence Scores (MES) framework, a robust system designed to maintain and enhance the quality of machine learning models at scale. We will unpack its core components—indicators, objectives, and agreements—and explain how they work together to ensure model reliability and performance. This framework enables Uber’s ML ecosystem to operate seamlessly and efficiently, driving both innovation and operational excellence.
For more details, you can refer to their published tech blog, linked here for your reference: https://www.uber.com/blog/enhancing-the-quality-of-machine-learning-systems-at-scale/ 

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