ml-pipeline

Builds reproducible machine-learning pipelines with feature engineering, tracked training, model validation, and deployment configuration.

When to use it

Use when building machine-learning pipelines, orchestrating training, automating model lifecycle workflows, or configuring experiment tracking and MLOps tooling.

Give it a pipeline implementation request for your project; it produces pipeline definitions, feature engineering, training, evaluation, and deployment code.