What Is Feature Engineering? Missing Values, One‑Hot Encoding & Scaling

Learn feature engineering in the simplest way possible!
In this video, I explain step by step:

What is feature engineering in machine learning
What are feature variables and target variables
Why we use feature engineering (and why it’s so important)
How to handle missing values in your dataset
How to use SimpleImputer to fill missing values
How to use OneHotEncoder to convert categories to numbers
How and why we do feature scaling (standardization / normalization)
A simple end‑to‑end example so beginners can follow easily

This video is made for absolute beginners, students, and anyone who wants to understand ML preprocessing in very simple words. No advanced math, just clear concepts and practical examples.

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