artifact-experiment

artifact-experiment constitutes the experiment orchestration extension to Artifact-ML.

It provides the tools to build reusable validation workflows with integrated tracking using popular backend services (e.g. Mlflow).

It stands alongside:

• artifact-core: a declarative interface for the computation of validation artifacts in ML experiments.
• artifact-torch: PyTorch integration for building reusable deep-learning workflows declaratively.

Topics

• Getting Started - quick installation instructions.
• User Guide — general user instructions.
• Architecture — high level framework architecture.
• Core Entities — framework core entity specification.
• Development Guide — low-level development guidelines.