Turn raw data into model-ready features.
What it does
Creates engineered datasets, transformation documentation, and preprocessing code for machine-learning models.
When to use it
Use when raw features need encoding, scaling, domain-specific transformations, or adjustments for skewed distributions and nonlinear relationships.
How to use it
Give it data to prepare for machine learning; it produces engineered features, analysis, documentation, and preprocessing pipeline code.
What you provide
- Your files
What you need · 6
The implementation uses Python; no runtime version is specified.
The implementation imports pandas for datasets and feature transformations.
The implementation imports numpy for numerical operations.
The implementation imports matplotlib.pyplot for visualizations.
Access · 0
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