How is unsupervised learning different from supervised learning?
Unsupervised learning works without output labels and finds patterns on its own.
Explanation:
- Supervised learning uses labeled data (input features with known output labels) to learn how to make predictions.
- Unsupervised learning uses unlabeled data and identifies hidden patterns, groups, or structures within the data without predefined outputs.
Example:
- Grouping customers based on purchasing behavior (clustering) is an unsupervised learning task.
