📊 Data Analysis
Feature Engineering
Feature engineering creates new signals from raw data. This section provides textbook precision on the 'Garbage In, Garbage Out' principle.
● Advanced
📖 Based on: Hands-On Machine Learning — Aurélien Géron
📋 Table of Contents
1 · Signal vs Noise
Textbook Definition
"Feature engineering means coming up with better features to help your ML model learn the underlying structure of the data. Successful models are often 80% data preparation." — Aurélien Géron
2 · Return Value: Log Transform
🔁 Return Value
Performing np.log1p() on a Series returns a new Series where skewed values are compressed into a more normal distribution, which is essential for many linear algorithms.