Skip to content

Digital Hub

Introduction
Overview and architecture
Quick Start
Installation
Concepts and Tasks
Concepts and Tasks
Components
Components
- Landing Page
- Core UI
- CLI
- Kubernetes Resource Manager
- KubeAI and OpenWebUI
- Interactive Workspaces
  Interactive Workspaces
  - Code Toolbox
  - Community Workspaces
    Community Workspaces
    
    Dremio
    
    SQLPad
    
    Grafana
Scenarios and Tutorials
Scenarios and Tutorials
- Introduction to scenarios
- Extract-Transform-Load
  Extract-Transform-Load
- DBT transformation
  DBT transformation
  - ETL with digitalhub-core and DBT scenario introduction
  - Workflow
- MLOps: Scikit-learn ML models
  MLOps: Scikit-learn ML models
- MLOps: MLflow ML models
  MLOps: MLflow ML models
  - MLFLow ML scenario introduction
  - Deploy and expose the model
- MLOps: Large Language Models
  MLOps: Large Language Models
  - Managing LLM Models
  - Managing LLM Models with KubeAI Runtime
- MLOps: Speech to Text
  MLOps: Speech to Text
  - Managing Speech-to-Text Models with KubeAI Runtime
- MLOps: Custom ML model training
  MLOps: Custom ML model training
  - Custom ML scenario introduction
  - Deploy and expose the model
- Dremio transformation
  Dremio transformation
  - Data transformation and usage with Dremio and Grafana
- API via PostgREST
  API via PostgREST
- Retrieval-Augmented Generation
  Retrieval-Augmented Generation
- Whisper fine-tuning
  Whisper fine-tuning
- Flower Federated Learning
  Flower Federated Learning
  - Federated Learning with Flower
- Data validation
  Data validation
  - Data validation
Runtimes reference
Runtimes reference
SDK Reference
SDK Reference
- Python SDK Reference
CLI Reference
CLI Reference
- CLI commands

Introduction to scenarios

This section showcases a number of different use cases for the platform.

Each scenario can be replicated by following its related section, but if you'd rather, you can check out our tutorials repository for any source code or notebooks that may be available.