Supervised Learning
A machine learning approach where models learn from labeled input-output pairs to predict outcomes on new data.
Supervised learning is the most common form of machine learning. You provide labeled examples β input data paired with the correct output β and the model learns a mapping from inputs to outputs.
Examples include image classification (photo β label), spam detection (email β spam/not spam), and price prediction (house features β price). The model improves by minimizing the difference between its predictions and the true labels.
Common supervised algorithms include linear regression, decision trees, random forests, support vector machines, and neural networks. Most production ML systems still use some form of supervised learning.