K Means Clustering, Hierarchical Clustering, Machine Learning, Dendrogram, Silhouette Score.
each data point is assigned to a single cluster. This makes it useful for exploratory data analysis and pattern recognition. Versatility: K-means clustering can work well with various types of data and distance metrics. It is not restricted to specific data types or assumptions about data