The MLOps Community fills the swiftly growing need to share real-world Machine Learning Operations best practices from engineers in the field.

MLOps Community is a collaborative platform for professionals working at the intersection of machine learning and operations, offering resources, events, and discussions on MLOps best practices and methodologies. By bringing together data scientists, engineers, and DevOps practitioners, MLOps Community enbles knowledge sharing and innovation in deploying, managing, and scaling machine learning models in production environments.

MLOps Community

Explore how to perform distributed training in MLOps using mixed AMD and NVIDIA GPU clusters. The post delves into overcoming vendor lock-in, unifying heterogeneous clusters, and leveraging AWS instances for efficient AI infrastructure. Learn about managing cluster heterogeneity, integrating PyTorch with UCX and UCC, and orchestrating Kubernetes for distributed machine learning workloads.

Distributed Training in MLOps

Break GPU Vendor Lock-In: Distributed MLOps across mixed AMD and NVIDIA Clusters

Enabling Heterogenous Kubernetes Clusters