Feature Engineer

Overview

Feature engineering often makes the difference between mediocre and excellent ML models. This skill transforms raw data into model-ready features through systematic data quality assessment, feature creation, selection, and transformation—all integrated with SpecWeave's increment workflow.

The Feature Engineering Pipeline

Phase 1: Data Quality Assessment

Before creating features, understand your data:

from specweave import DataQualityReport

# Automated data quality check
report = DataQualityReport(df, increment="0042")

# Generates: