FinAI Summit 2025: Create and speed up your ML solution with Mercury

Build robust, efficient, and scalable machine learning pipelines with modern tools and best practices.

Get ready for the masterclass!

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About the masterclass

This masterclass offers a practical walkthrough of a complete MLOps workflow using Amazon SageMaker. Participants will learn how to work with feature stores, distinguish between offine and online layers for training and inference, register and deploy models, and monitor performance through real-time data capture and drift detection—ensuring long-term model quality. In addition, the session introduces Mercury, an open-source library designed to accelerate the development of machine learning solutions. Through a real-world use case, participants will explore Mercury’s modular architecture and work hands-on with key components such as Robustness, Explainability, and Monitoring. This session is ideal for data scientists and ML engineers looking to streamline model development and adopt scalable, production-ready workflows