Customer Segmentation Using Unsupervised Machine Learning Algorithms
-
Updated
Jul 10, 2023 - Jupyter Notebook
Customer Segmentation Using Unsupervised Machine Learning Algorithms
Successfully performed unsupervised clustering on student social network profiles to identify behavior patterns and group similarities, aiding in personalized engagement and targeted academic interventions.
Data Mining - EDA, Feature Selection, Standardize, Remove Global Outliers, Normalize, Feature Extraction (with PCA), Clustering, Classification (baseline models and hyperparameter tuning with GridSearchCV).
This repository implements customer segmentation techniques to analyze credit card user behavior and identify distinct customer groups. By leveraging Python libraries like pandas, Scipy and scikit-learn.
Add a description, image, and links to the gaussian-mixture-clustering topic page so that developers can more easily learn about it.
To associate your repository with the gaussian-mixture-clustering topic, visit your repo's landing page and select "manage topics."