Seldon Core is an open source platform for deploying machine learning models on a Kubernetes cluster.

• Deploy machine learning models in the cloud or on-premise.
• Get metrics and ensure proper governance and compliance for your running machine learning models.
• Create powerful inference graphs made up of multiple components.
• Provide a consistent serving layer for models built using heterogeneous ML toolkits.

• Lets you focus on your model by making it easy to serve on kubernetes
• The same workflow and base API for a range of toolkits such as scikit-learn, tensorflow and R
• Out of the box best-practices for logging, tracing and base metrics, applicable to all models across toolkits
• Support for deployment strategies such as running A/B test and canaries
• Inferences graphs for microservice-based serving strategies such as multi-armed bandits or pre-processing

Documentation can be found here.

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