Deploying models (to tractors 🚜)
Practical AI
Collaborative MLOps: Enhancing Model Deployment with Kubernetes
This chapter explores the collaboration among teams to improve model training and deployment processes using ClearML and Kubernetes. It discusses the challenges of server management, resource scheduling, and the integration of MLOps with Kubernetes in the context of agricultural technology. The conversation highlights the development of flexible solutions for model serving, data management, and the importance of community-driven features to enhance visibility and job handling.
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