Data Preprocessing Pipeline

소개

This skill empowers Claude to architect and execute robust data preprocessing pipelines, ensuring high-quality data readiness for machine learning projects. By automating repetitive tasks such as handling missing values, removing duplicates, and transforming raw sensor or customer data into structured formats, it streamlines the data preparation phase while incorporating industry best practices for validation and error handling.

주요 기능

• Seamless transformation of raw data into ML-ready formats
• Real-time data validation and error handling logic
• Automated data cleaning and missing value imputation
• End-to-end ETL pipeline generation and execution
• 883 GitHub stars
• Comprehensive performance metrics and data quality reporting

사용 사례

• Cleaning customer datasets by removing duplicates and handling null values
• Building ETL pipelines to convert database logs into time-series data
• Standardizing disparate data sources for model training and evaluation