Get started
From Giskard installation to collaborative ML evaluation and testing
Open-Source CI/CD platform for ML teams. Deliver ML products, better & faster.
  • Collaborate faster with feedback from business stakeholders.
  • Deploy automated tests to eliminate regressions, errors & biases.
GitHub - Giskard-AI/giskard: Quality Assurance for AI
GitHub
Join the Giskard Discord Server!
Discord

Setup

git clone https://github.com/Giskard-AI/giskard.git
cd giskard
docker-compose up -d
Yes, that's all! Then start inspecting & testing your ML models at http://localhost:19000/
login: admin password: admin
For more details, refer to the guides below:

Workflow

1. Validate your ML model by collecting feedback

AI Inspect Session

2. Discuss and analyze feedback

Feedback on ML model

3. Turn feedback into tests

Automated ML Testing with Giskard

Guides: Jump right in

Follow our handy guides to get started on the basics as quickly as possible:

License

This project is licensed under the terms of the Apache Software License 2.0 license. See LICENSE for more details.
Export as PDF
Copy link
Edit on GitHub
Outline
Setup
Workflow
1. Validate your ML model by collecting feedback
2. Discuss and analyze feedback
3. Turn feedback into tests
Guides: Jump right in
License