Feature Engineering

Feature engineering is the process of transforming raw data into features that better represent the underlying problem to the predictive models, resulting in improved model accuracy. This involves selecting, transforming, and creating new features from existing data. The goal is to extract more information from the data and make it easier for machine learning algorithms to learn patterns and make accurate predictions.

Visit the following resources to learn more:

• @article@What is a feature engineering? | IBM
• @article@Feature Engineering in Machine Learning: A Practical Guide
• @video@What is feature engineering | Feature Engineering Tutorial Python