Data Preprocessing Pipeline

Positioning

In governed ML routing, treat this skill as a stage assistant. It is for preprocessing-heavy execution after the pack owner is chosen.

When to Use

Use this skill when:

• Prepare raw data for machine learning models.
• Automate data cleaning and transformation processes.
• Implement a robust ETL (Extract, Transform, Load) pipeline.

Not For / Boundaries

• Whole-task ML ownership: use

  scikit-learn

  ,

  ml-pipeline-workflow

  , or

  training-machine-learning-models

• Leakage and prediction-time auditing: use

  ml-data-leakage-guard

• Grouped scientific preprocessing with stronger methodological constraints: use

  scientific-data-preprocessing

Typical Outputs

• A preprocessing pipeline plan or implementation sketch
• Clear sequencing for clean, encode, transform, and validate steps
• Handoff notes for leakage review, training, or evaluation

Related Skills

• ml-data-leakage-guard

  before trusting fitted preprocessing steps

• splitting-datasets

  when the next narrow problem is partition strategy