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ml-pipeline-orchestration - ML Pipeline Orchestration for GPU Workflows

Design and orchestrate ML pipelines with GPU steps and artifact tracking

Tags

Updated: 2026-03-24
MLOpsML pipelinesorchestrationGPUMetaflowKubeflowZenML

Capabilities

select orchestratordesign pipeline flowconfigure GPU resourcesingest dataset

Typical Inputs

datasethyperparametersGPU resources

Typical Outputs

trained modelmodel metricsmodel URI

What this skill does

  • select orchestrator
  • design pipeline flow
  • configure GPU resources
  • ingest dataset
  • preprocess data
  • train model
  • evaluate model
  • register model
  • track experiments
  • parallel training

Inputs

  • dataset
  • hyperparameters
  • GPU resources
  • Docker image
  • registry credentials

Outputs

  • trained model
  • model metrics
  • model URI
  • experiment artifacts
  • pipeline run status

Requirements

  • Container support
  • GPU infrastructure
  • Object storage
  • Python 3.x
  • Orchestrator runtime

Source

  • Spec: SKILL.md

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