This repository showcases a Customer Segmentation project that leverages Machine Learning algorithms to categorize customers based on their purchasing behaviors. The goal is to uncover hidden patterns, enabling businesses to create targeted marketing strategies and personalized experiences.
- Data Preprocessing: Cleaning and transforming raw data for model readiness.
- Clustering Algorithms: Implementation of popular clustering techniques such as K-Means, DBSCAN, and Agglomerative Clustering.
- Feature Selection: Identifying and using key features for better segmentation.
- Visualization: Visualizing segmented customer groups for clear insights.
- Model Evaluation: Utilizing metrics like Silhouette Score and Davies-Bouldin Index to assess clustering performance.
- Python
- Pandas
- Scikit-Learn
- Matplotlib
- Seaborn