Unsupervised learning Algorithm in Clustering: A Comparison of Hierarchical and K-means

Unsupervised learning algorithms play a crucial role in discovering hidden patterns and structures within the data This paper delves into two prominent clustering approaches K-means and Hierarchical clustering.Evaluating their performance, strengths and weakness and their methodology and their process.The results highlight the strength of Hierarchical clustering in identifying complex clusters and k-means in handling well separated clusters.This study provides the insights for choosing the suitable algorithm for specific clustering tasks.