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GitHub - SeldonIO/seldon-core: Machine Learning Deployment for Kubernetes
source link: https://github.com/SeldonIO/seldon-core
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readme.md
Seldon Core 
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.
So Why Seldon?
- Let's 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
Documentation can be found here.
Community
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