{
  "id": "lib-process:data-science-ml--model-training-pipeline",
  "_kind": "LibraryProcess",
  "_file": "generated-library/processes.yaml",
  "_cluster": "generated-library",
  "attributes": {
    "displayName": "model-training-pipeline",
    "description": "Model Training Pipeline with Experiment Tracking - Execute model training with hyperparameter tuning,\ntrack experiments with metrics and artifacts, compare model variants, and select best performers with automated\nquality gates and convergence criteria.",
    "libraryPath": "library/specializations/data-science-ml/model-training-pipeline.js",
    "specialization": "data-science-ml",
    "references": [
      "- MLflow Experiment Tracking: https://mlflow.org/\n- Weights & Biases: https://wandb.ai/\n- Kubeflow Pipelines: https://www.kubeflow.org/\n- TensorFlow: https://www.tensorflow.org/\n- PyTorch: https://pytorch.org/\n- Scikit-learn Model Selection: https://scikit-learn.org/stable/model_selection.html\n- Optuna Hyperparameter Optimization: https://optuna.org/"
    ],
    "example": "const result = await orchestrate('specializations/data-science-ml/model-training-pipeline', {\n  projectName: 'Churn Prediction Model',\n  modelType: 'classification',\n  trainingData: 'data/train.csv',\n  validationData: 'data/val.csv',\n  targetMetric: 'f1_score',\n  targetPerformance: 0.85,\n  maxIterations: 10,\n  hyperparameterStrategy: 'bayesian'\n});",
    "usesAgents": [
      "general-purpose"
    ]
  },
  "outgoingEdges": [
    {
      "from": "lib-process:data-science-ml--model-training-pipeline",
      "to": "domain:data-science",
      "kind": "lib_applies_to_domain",
      "attributes": {
        "weight": 1
      }
    },
    {
      "from": "lib-process:data-science-ml--model-training-pipeline",
      "to": "workflow:release-management",
      "kind": "lib_implements_workflow",
      "attributes": {
        "weight": 1
      }
    },
    {
      "from": "lib-process:data-science-ml--model-training-pipeline",
      "to": "workflow:data-pipeline-deployment",
      "kind": "lib_implements_workflow",
      "attributes": {
        "weight": 0.7
      }
    },
    {
      "from": "lib-process:data-science-ml--model-training-pipeline",
      "to": "specialization:data-science-ml",
      "kind": "lib_belongs_to_specialization",
      "attributes": {
        "weight": 0.9
      }
    }
  ],
  "incomingEdges": []
}