A single frame summary of 6 types of clustering algorithms.

Centroid-based is the most common class of clustering. Yet, there's a whole world of algorithms beyond that, which we all should be aware of.

- Centroid-based: Cluster data points based on proximity to centroids.

- Connectivity-based: Cluster points based on proximity between clusters.

- Density-based: Cluster points based on their density. It is more robust to clusters with varying densities and shapes than centroid-based clustering.

- Graph-based: Cluster points based on graph distance.

- Distribution-based: Cluster points based on their likelihood of belonging to the same distribution.

- Compression-based: Transform data to a lower dimensional space and then perform clustering
