Introduction to Clustering Algorithms
Basics of grouping and clustering.
1
Introduction to Clustering Algorithms
Clustering is an unsupervised learning technique used to group similar data points together. Unlike supervised learning, clustering works without labeled data.
It is widely used in market segmentation, image compression, and recommendation systems.
2
What is Clustering?
Clustering aims to divide data into groups (clusters) such that:
- Data points within a cluster are similar to each other.
- Data points in different clusters are distinct from each other.
For example, clustering can group customers based on their purchasing behavior.
All lessons in this course
- Introduction to Clustering Algorithms
- K-Means Clustering
- K-Means Clustering Project
- Dimensionality Reduction Basics
- Dimensionality Reduction Application