From Text to Tables: Feature Engineering with LLMs for Tabular Data

📰 Machine Learning Mastery

LLMs can be used for feature engineering on complex datasets like tabular data

intermediate Published 10 Mar 2026

Action Steps

Identify complex datasets that can benefit from feature engineering
Use LLMs to generate new features or transform existing ones
Evaluate the performance of models using the engineered features
Refine the feature engineering process based on the results

Who Needs to Know This

Data scientists and machine learning engineers can benefit from using LLMs for feature engineering, as it can improve the accuracy of their models and reduce manual effort

Key Insight

💡 LLMs can automate and improve feature engineering for tabular data