Red Hat SummitRed Hat OpenShift AI Cloud Service 1
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Welcome
リリースノート
このリリースに関連する機能、機能拡張、解決された問題、および既知の問題
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
Supported configurations
Supported software platforms and architecture
Service definition
A complete overview of the features and limitations of the product
Product life cycle
Understand the product life cycle to plan deployments and support applications using the product
Red Hat AI learning hub
Explore a curated collection of learning resources designed to help you accomplish key tasks with Red Hat AI products and services
Provide feedback on Red Hat documentation
Let Red Hat know how we can make our documentation better
Documentation for OpenShift cluster administrators
Installing and uninstalling OpenShift AI Cloud Service
Install and uninstall OpenShift AI on an OpenShift Dedicated or Red Hat OpenShift Service on AWS cluster
Upgrading OpenShift AI Cloud Service
Upgrade OpenShift AI on an OpenShift Dedicated or Red Hat OpenShift Service on AWS cluster
OpenShift AI の管理
OpenShift AI を管理するためのクラスター管理者のタスク
モデルレジストリーコンポーネントの有効化
Red Hat OpenShift AI Cloud Service でモデルレジストリーコンポーネントを有効にする
Working with machine learning features (Technology Preview)
Install and manage Feature Store as a component in the Red Hat OpenShift AI Operator configuration
Enabling LAB-tuning (Technology Preview)
Enable model customization with LAB-tuning
Usage data collection notice
Understand the data Red Hat collects about your cluster usage
Documentation for OpenShift AI administrators
Managing resources
Manage cluster resources, Jupyter notebooks, and data backup in OpenShift AI
Working with RAG (Developer Preview)
Working with RAG in Red Hat OpenShift AI Cloud Service
アクセラレーターの使用
Red Hat OpenShift AI Cloud Service のアクセラレーターの使用
モデルレジストリーの管理
Red Hat OpenShift AI Cloud Service でのモデルレジストリーの管理
Documentation for OpenShift AI users
Getting started with Red Hat OpenShift AI Cloud Service
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
S3 互換オブジェクトストアでのデータの使用
ワークベンチから S3 互換オブジェクトストアに保存されたデータを使用する
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
データサイエンス IDE での作業
Red Hat OpenShift AI Cloud Service からのデータサイエンス IDE での作業
データサイエンスパイプラインの使用
Red Hat OpenShift AI Cloud Service のデータサイエンスパイプラインを活用する
Customizing models with LAB-tuning (Technology Preview)
Customize models with LAB-tuning
データサイエンスモデルの監視
OpenShift AI モデルの公平性を監視する
分散ワークロードの使用
分散ワークロードを使用して、データ処理とモデルトレーニングのさらなる高速化および効率化を実現する
接続されたアプリケーションの使用
Red Hat OpenShift AI Cloud Service からアプリケーションに接続する
モデルレジストリーの操作
Red Hat OpenShift AI Cloud Service でのモデルレジストリーの操作
Serving models
Serve models in OpenShift AI
API tiers
View a list of API tiers and API version examples for OpenShift AI
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