End-to-End Unsupervised Learning Pipeline (v5.0). Segments customers using Omnichannel RFM analysis & Auto-Tuned K-Means. Features a Dockerized FastAPI service and Streamlit dashboard.

Predicting bank term deposit subscriptions using Gradient Boosting, feature importance analysis, and customer segmentation for targeted marketing.

A machine learning app that segments customers into distinct groups based on behavior or demographics using clustering or classification techniques.

A journey through understanding customer segmentation using python with the general goal of encouraging data driven decision making

customer segmentation via RFM analysis

Datasets from InstaCart provide a relational set of files describing customers' orders over time, and contains a sample of over 3 million grocery orders from more than 200,000 Instacart users.

Customer enrolment prediction

Udacity Machine Learning Engineer Nanodegree, Unsupervised learning project (Nov 2018)

This is a case study in my Data Analyst Path by Miuul.

Built an interactive Power BI dashboard to analyze employee attrition, satisfaction, and performance trends for strategic HR insights.

SegmentWise: Unveiling Customer Insights for Exploratory Data Analysis (EDA) and Customer Segmentation

Create a classifier model to identify group of customer using deep learning and return result in a new csv file

Unsupervised learning model (K-Means) for customer segmentation using RFM analysis to drive targeted marketing campaigns.

K-Means kümeleme yöntemine uygun olarak yapılmış bir segmentasyon projesi

Customer Segmentation Using K-Means Clustering

Este es un proyecto de Data Science en el que aplicaremos: EDA + Métodos de Clustering

Customer Segmentation using K-means clustering for targeted marketing insights

Advanced K-Means clustering system for customer analytics and segmentation using machine learning. Includes RFM analysis, business insights, and actionable marketing strategies.

In this project, we will first firstly implement RFM Analysis to group customers according to RFM metrics and then the same customers will be segmented by using K-Means and Hierarchical Clustering algortihms.