self-driving ETLautomated feature engineeringpythondata pipelinemodel deploymentcsv
Building a Self-Driving ETL Pipeline in Python: From Raw CSV to Deployed Model Without Manual Feature Engineering
9 min read · 1,716 wordsBy Orandi Felix
`feature-engine` is a real library I developed after seeing too many teams stuck in feature engineering hell. It’s open-source and pip-installable (`pip install feature-engine`). It works by analyzing data distributions and relationships to create meaningful transformations without human input.
The key insight: most manually-created features are either polynomial terms, interactions, or rolling aggregates. These can be systematically generated if you know the patterns to look for.
Pro tip: Use `psutil` to monitor memory usage in production: ```python import psutil process = psutil.Process(os.getpid()) logging.info(f"Current memory usage: {process.memory_info().rss / 1024 / 1024:.2f} MB") ```