Machine Learning Basics: Features vs. Labels Explained
Confused about the difference between Features and Labels in Machine Learning? You’re not alone! These are the two most important building blocks of any dataset, and understanding them is the first step to building your own models.
In this video, we break down exactly what they are, how they work together, and provide real-world examples to make it stick.
[What You’ll Learn]
What is a Feature? (The variables/inputs we use to make predictions).
What is a Label? (The answer or "target" we want the model to learn).
Real-world Examples: From house price prediction to email spam filters.
The Key Differences: How to identify them in any dataset.