Experience with an End-to-End MLOps Pipeline - Practical Insights and 3D Architectural Perspectives
MLCon | Machine Learning Conference via YouTube
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Explore the practical challenges and solutions of building a reliable end-to-end MLOps pipeline through real-world implementation experiences shared by René Brunner and Eric Joachim Liese in this 53-minute conference talk from MLCon. Discover how to design and optimize complete MLOps workflows from data preparation and model training through deployment and monitoring, while learning how 3D architectural perspectives can enhance AI workflows and streamline processing for more efficient model management. Gain insights into key technical and operational decisions, success factors, and proven best practices essential for running MLOps systems in production environments, including lessons learned from actual implementation challenges and architectural considerations for modern AI development workflows.
Syllabus
Experience with an end-to-end MLOps pipeline: Practical insights and 3D architectural perspectives
Taught by
MLCon | Machine Learning Conference