Feature Engineering Explained (ML Exam Must-Know!)
Автор: Ai Cloud Path
Загружено: 2026-01-18
Просмотров: 4
Описание:
Feature engineering is one of the most important — and most tested — concepts in machine learning.
In this lesson, we break down what feature engineering is, why it matters, and how it transforms raw data into something machine learning models can actually learn from. You’ll walk through real-world examples like auto loan datasets and understand key techniques such as:
✔ Feature selection
✔ Feature extraction
✔ Dimensionality reduction (PCA concepts)
✔ Categorical encoding
✔ Normalization vs standardization
This video is exam-focused, so you don’t need to memorize formulas — just understand when and why each technique is used.
If you’re studying for an AI, ML, or AWS certification, this lesson will help you confidently answer feature-engineering questions and understand how models learn more effectively from data.
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