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https://github.com/bvobart/ml-drift-detection-kubernetes

Created during MLE Chapter day in an attempt to try and run the code from this article: https://towardsdatascience.com/production-machine-learning-monitoring-outliers-drift-explainers-statistical-performance-d9b1d02ac158
https://github.com/bvobart/ml-drift-detection-kubernetes

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Created during MLE Chapter day in an attempt to try and run the code from this article: https://towardsdatascience.com/production-machine-learning-monitoring-outliers-drift-explainers-statistical-performance-d9b1d02ac158

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# ml-drift-detection-kubernetes
Created during MLE Chapter day in an attempt to try and run the code from this article: https://towardsdatascience.com/production-machine-learning-monitoring-outliers-drift-explainers-statistical-performance-d9b1d02ac158

## Pre-requisites

- Python 3.8 (3.9 will not work with Tensorflow and alibi-detect)
- [Minikube](https://minikube.sigs.k8s.io/)
- [Poetry](https://github.com/python-poetry/poetry) - `pip install poetry`

## How to use this?

### Prepare Kubernetes environment

1. Run `minikube start` to start up a local Kubernetes
2. Install [Knative](https://knative.dev/docs/install/install-eventing-with-yaml/) Eventing to the K8s cluster:
```sh
kubectl apply -f https://github.com/knative/eventing/releases/download/v0.22.0/eventing-crds.yaml
kubectl apply -f https://github.com/knative/eventing/releases/download/v0.22.0/eventing-core.yaml
```
3. Install [Seldon Core](https://github.com/SeldonIO/seldon-core/#install-seldon-core) to the K8s cluster:
```
kubectl create namespace seldon-system

helm install seldon-core seldon-core-operator \
--repo https://storage.googleapis.com/seldon-charts \
--set usageMetrics.enabled=true \
--namespace seldon-system \
--set ambassador.enabled=true
```

### Prepare project

1. Clone this repository: `git clone git@github.com:bvobart/ml-drift-detection-kubernetes.git`
2. `poetry install`