K Means Clustering, Hierarchical Clustering, Machine Learning, Dendrogram, Silhouette Score.
Data: K-means clustering works well with numeric data, as it relies on calculating distances between data points. It is suitable for continuous variables or attributes that can be represented numerically. Quick Prototyping and Exploration: Due to its simplicity and ease of implementation, K-means