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- WIP : PySpark and PMML example [\#155](https://github.com/SeldonIO/seldon-core/pull/155) ([cliveseldon](https://github.com/cliveseldon))
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- Fix gRPC tests for wrappers and update sklearn iris example to show use [\#150](https://github.com/SeldonIO/seldon-core/pull/150) ([cliveseldon](https://github.com/cliveseldon))
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- Minikube RBAC updates and Notebooks for Model examples [\#147](https://github.com/SeldonIO/seldon-core/pull/147) ([cliveseldon](https://github.com/cliveseldon))
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- change ClusterRoleBinding to RoleBinding [\#146](https://github.com/SeldonIO/seldon-core/pull/146) ([gsunner](https://github.com/gsunner))
- Openshift article on using s2i in seldon-core [\#140](https://github.com/SeldonIO/seldon-core/pull/140) ([cliveseldon](https://github.com/cliveseldon))
Copy file name to clipboardExpand all lines: docs/getting_started/minikube.md
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@@ -213,12 +213,4 @@ The response contains:
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*"names": The names of your classes.
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*"ndarray": The predicted probabilities for each class.
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## Next Steps
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* You can run several notebooks that show various examples on minikube and Google cloud platform
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* [Jupyter Notebook showing deployment of prebuilt model using Minikube](https://github.com/SeldonIO/seldon-core/blob/master/notebooks/kubectl_demo_minikube.ipynb)
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* [Jupyter Notebook showing deployment of prebuilt model using GCP cluster](https://github.com/SeldonIO/seldon-core/blob/master/notebooks/kubectl_demo_gcp.ipynb)
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* [Epsilon-greedy multi-armed bandits for real time optimization of models](https://github.com/SeldonIO/seldon-core/blob/master/notebooks/epsilon_greedy_gcp.ipynb)
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* [Advanced graphs showing the various types of runtime prediction graphs that can be built](https://github.com/cliveseldon/seldon-core/blob/master/notebooks/advanced_graphs.ipynb)
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* [Jupyter notebook to create seldon-core with ksonnet and expose APIs using Ambassador.](https://github.com/SeldonIO/seldon-core/blob/master/notebooks/ksonnet_ambassador_minikube.ipynb)
@@ -49,8 +47,8 @@ public SeldonMessage aggregate(List<SeldonMessage> outputs, PredictiveUnitState
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if (shape.length!=2){
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thrownewAPIException(APIException.ApiExceptionType.ENGINE_INVALID_COMBINER_RESPONSE, String.format("Combiner received data that is not 2 dimensional"));
for (Iterator<SeldonMessage> i = outputs.iterator(); i.hasNext();)
@@ -69,10 +67,10 @@ public SeldonMessage aggregate(List<SeldonMessage> outputs, PredictiveUnitState
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if (inputShape[1] != shape[1]){
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thrownewAPIException(APIException.ApiExceptionType.ENGINE_INVALID_COMBINER_RESPONSE, String.format("Expected batch length %d but found %d",shape[1],inputShape[1]));
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