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Add e2e tutorial for fraud detection #2550

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Mar 1, 2024
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Original file line number Diff line number Diff line change
Expand Up @@ -27,7 +27,7 @@ describe('ManageInferenceServiceModal', () => {
const currentProject = mockProjectK8sResource({});
const wrapper = render(
<ManageInferenceServiceModal
isOpen={true}
isOpen
projectContext={{
currentProject,
dataConnections: [],
Expand All @@ -51,7 +51,7 @@ describe('ManageInferenceServiceModal', () => {
await act(async () => {
wrapper.rerender(
<ManageInferenceServiceModal
isOpen={true}
isOpen
projectContext={{
currentProject: projectChange,
dataConnections: [],
Expand Down
1 change: 1 addition & 0 deletions manifests/overlays/apps/base/rhoai/kustomization.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -5,3 +5,4 @@ commonLabels:
app.kubernetes.io/part-of: odh-dashboard
resources:
- rhoai-app.yaml
- rhoai-docs.yaml
15 changes: 15 additions & 0 deletions manifests/overlays/apps/base/rhoai/rhoai-docs.yaml
Original file line number Diff line number Diff line change
@@ -0,0 +1,15 @@
apiVersion: dashboard.opendatahub.io/v1
kind: OdhDocument
metadata:
name: rhoai-tutorial-fraud
annotations:
opendatahub.io/categories: 'Getting started,Model training,Notebook environments,Pipelines'
spec:
displayName: OpenShift AI tutorial - Fraud detection example
appName: rhoai
type: how-to
description: |-
Use OpenShift AI to develop and train an example model in Jupyter Notebooks, deploy the model, integrate the model into a fraud detection application, and refine the model by using automated pipelines.
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@MelissaFlinn MelissaFlinn Mar 1, 2024

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Can we change the description to:
Use OpenShift AI to train an example model in a Jupyter notebook, deploy the model, integrate the model into a fraud detection application, and refine the model by using automated pipelines.

url: https://access.redhat.com/documentation/en-us/red_hat_openshift_ai_cloud-service/1/html-single/openshift_ai_tutorial_-_fraud_detection_example/
durationMinutes: 60
---
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