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.
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Updated
Nov 25, 2025 - Python
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.
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
K-Means kümeleme yöntemine uygun olarak yapılmış bir segmentasyon projesi
SegmentWise: Unveiling Customer Insights for Exploratory Data Analysis (EDA) and Customer Segmentation
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
Udacity Machine Learning Engineer Nanodegree, Unsupervised learning project (Nov 2018)
Built an interactive Power BI dashboard to analyze employee attrition, satisfaction, and performance trends for strategic HR insights.
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.
Customer segmentation using K-Means clustering and t-SNE visualization for better customer insights.
Customer Segmentation using K-Means Clustering
computer vision model to detect hand and take order based on hand detection
🚀 Advanced Customer Segmentation & Marketing Intelligence Platform - Transform your customer data into actionable insights with AI-powered RFM analysis
🎥 Generate high-quality video editing data with Ditto, a scalable pipeline that trains advanced instruction-based editing models.
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
Supply-chain efficiency analytics in Power BI with SQL and Python integration.
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