Experience with an end-to-end MLOps pipeline: Practical insights and 3D architectural perspectives
Автор: MLCon | Community & Conferences
Загружено: 2025-11-12
Просмотров: 41
Building a reliable end-to-end MLOps pipeline is no small task — it’s a journey full of technical, architectural, and operational challenges. In this talk, René Brunner and Eric Joachim Liese share real-world experiences implementing a complete MLOps pipeline, from data preparation and model training to deployment and monitoring.
Learn how integrating a 3D architecture can enhance your AI workflows, streamline processing, and enable more efficient model management. The speakers also dive into key decisions, success factors, and best practices for running MLOps in production environments.
🔍 You’ll Learn:
How to design and optimize an end-to-end MLOps pipeline
How 3D architectures integrate into modern AI workflows
Lessons learned from real-world implementation
Best practices for production-ready MLOps
#MLOps #MachineLearning #AI #DataEngineering #MLcon #AIDevelopment #AIArchitecture
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