Artificial Intelligence & Machine Learning
Unsupervised Learning
Definition
Unsupervised learning is a type of machine learning where the model is trained on an unlabeled dataset. The model tries to find patterns, structures, and relationships within the data on its own.
Why It Matters
Unsupervised learning is powerful for exploring data and discovering hidden insights when you don't have pre-existing labels. It can find natural groupings and anomalies in data.
Contextual Example
A company might use unsupervised learning (specifically, clustering) on its customer data to identify distinct market segments. The algorithm would group similar customers together based on their purchasing behavior, without any prior knowledge of what the segments should be.
Common Misunderstandings
- Clustering (grouping similar data points) and dimensionality reduction (reducing the number of variables) are the two main types of unsupervised learning.
- It is often used in the exploratory phase of data analysis.