The objective of this project is to analyze the customers of a bank, categorize them with K-Means and Hierarchical Clustering and evaluate their distinct characteristics

Customer Segmentation using K-Means Clustering to identify distinct groups based on purchasing behaviour, enabling targeted marketing strategies for an online retail business.

Analyze the stocks data, grouping the stocks based on the attributes provided, and sharing insights about the characteristics of each group.

Classification Model of Potential Credit Card Customers

Analyze the stocks data, grouping the stocks based on the attributes provided, and sharing insights about the characteristics of each group.

Unsupervised Learning: Analyze the stocks data, grouping the stocks based on the attributes provided, and sharing insights about the characteristics of each group.

Customer segmentation of retail data using PCA + K-Means, Agglomerative, and DBSCAN/HDBSCAN, with cluster profiling via radar charts and histograms, and cluster-based top-3 product recommendations.