MLGraph defines a graph of machine learning components. The goal is to provide a simple machine learning focused specification for defining:

• Easy model Experimentation and AB tests
• Advanced routing with Multi-Armed Bandits
• Ensembling of models
• Explanations, Outlier Detection, Skew and Bias detection
• Builds upon KFServing and other ML Serving Components
• Flexible graph nodes:
  • References or inline specs
• Custom user provided components *Auto-validation of graph

An example graph:

• Control plane
  • Examples
• Data plane

There could be multiple implementations of the spec. The initial focus will be build upon KNative.

• A KNative implementation proposal
• An Apache Arrow proposal

The spec is a live document.

• Discussion Points