Product Documentation for Red Hat OpenShift AI Self-Managed 2.8
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Product documentation for Red Hat OpenShift AI Cloud Service
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Welcome
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Release notes
Features, enhancements, resolved issues, and known issues associated with this release -
Introduction to Red Hat OpenShift AI
OpenShift AI is a platform for data scientists and developers of artificial intelligence and machine learning (AI/ML) applications -
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Documentation for ML Ops Engineers and Data Scientists
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Getting started with Red Hat OpenShift AI Self-Managed
Learn how to work in an OpenShift AI environment -
OpenShift AI tutorial - Fraud detection example
Use OpenShift AI to train an example model in a Jupyter notebook, deploy the model, and refine the model by using automated pipelines -
Integrating data from Amazon S3
Use data stored in an Amazon Web Services (AWS) Simple Storage Service (S3) bucket -
Working on data science projects
Organize your work in projects and workbenches, create and collaborate on notebooks, train and deploy models, configure model servers, and implement pipelines -
Serving models
Serve models in OpenShift AI -
API tiers
View a list of API tiers and API version examples for OpenShift AI
Documentation for OpenShift AI administrators
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Managing users
Manage user permissions in OpenShift AI -
Managing resources
Manage cluster resources, Jupyter notebooks, and data backup in OpenShift AI
Documentation for IT Operations administrators
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Supported configurations
Supported software platforms and architecture -
Installing and uninstalling OpenShift AI Self-Managed
Install and uninstall Red Hat OpenShift AI -
Installing and uninstalling OpenShift AI Self-Managed in a disconnected environment
Install and uninstall Red Hat OpenShift AI in a disconnected environment -
Upgrading OpenShift AI Self-Managed
Upgrade OpenShift AI on OpenShift Container Platform -
Upgrading OpenShift AI Self-Managed in a disconnected environment
Upgrade Red Hat OpenShift AI on OpenShift Container Platform in a disconnected environment