Unsupervised Learning – Final Task
Implemented an unsupervised learning project applying techniques such as clustering (K-Means, Hierarchical, DBSCAN) and dimensionality reduction (PCA) to uncover hidden patterns and groupings within unlabeled datasets. The task demonstrated skills in data preprocessing, feature engineering, model selection, and evaluation using metrics such as silhouette score and Davies-Bouldin index