Feature Engineering | Customer Churn Clasification | Python

Your machine learning algorithm might not be the problem—it’s the information you’re feeding it! In this tutorial, you’ll take messy customer churn data, engineer meaningful new features, and see if those features actually improve your model's accuracy What You’ll Learn: What feature engineering is (and why raw data isn't enough) How to create interaction features, ratios, and binary flags Handling categorical data with One-Hot Encoding Log transformations & feature scaling (StandardScaler) How to avoid Data Leakage using Scikit-Learn Pipelines Colab Notebook Link: https://colab.research.google.com/dri...