Day 8 Feature Engineering

Most beginners spend hours tweaking hyperparameters, but true experts spend their time on Feature Engineering. Why? Because a model is only as smart as the information you give it. Today, we move beyond basic cleaning to start "crafting" high-signal features that can drastically boost your model's accuracy.
What you’ll learn:
Domain Knowledge: Transforming raw variables (like "Date") into actionable insights (like "Is_Weekend" or "Days_Since_Event").
Polynomial Features: How to mathematically combine features to capture non-linear relationships.
Target Encoding: Advanced techniques for handling high-cardinality categorical data (like Zip Codes) without creating thousands of dummy columns.
Aggregations: Creating summaries that provide context to your individual data points.
Challenge: Look at your dataset. Find one relationship between two columns, create a new "engineered" feature out of it, and see if it improves your model's F1 score compared to the raw data.

#machinelearning #featureengineering #datascience #datapreprocessing #python #ai #datamodeling

Видео Day 8 Feature Engineering канала Professor Answers