Artificial Intelligence with Python 3- Label Encoding & One‑Hot Encoding

Ready to take your machine learning preprocessing to the next level? In this video, we dive into two essential data‑wrangling techniques that power every robust model:

Label Encoding & One‑Hot Encoding: Learn how to turn categorical labels into numeric formats your algorithms can understand—whether it’s compressing target classes with LabelEncoder or expanding categories into clear, non‑ordinal OneHot vectors.

Feature Scaling: Discover why scaling your training data is crucial, and walk through hands‑on demos of Min‑Max and Standard Scalers to ensure every feature plays fair in gradient descent and distance‑based models.

You’ll see real datasets in action, step‑by‑step coding examples in Python, and pro tips on when to choose each encoder or scaler.