Unsupervised ML: Finding Customer Segments in General Population

Customer segmentation using k-modes unsupervised clustering

Unsupervised learning techniques applied on product spending data collected for customers of a wholesale distributor to identify customer segments hidden in the data.

This repository contains project materials for the Spring 2024 STAT 208 class, specifically for Team 8. All materials are the property of Team 8, University of California, Riverside, A. Gary Anderson School of Management. Thank you for viewing our repository.

Identifying customer segments for mail-orders company and performing a comparison with the general population

In this project, I will be performing an unsupervised clustering of customer's records from a Retail Chain.

This project involves a comprehensive Customer Segmentation Analysis for an Australian bike company. The analysis uses RFM model to categorize customer and visualise key metrics, aiming to enhance sales strategies and customer engagement.

This repository contains code for my Machine Learning Basic Nanodegree Project.

Udacity Machine Learning Engineer Nanodegree Capstone on customer segmentation and acquisition with Arvato Bertelsmann Financial Solutions.

This project analyzes e-commerce order fulfillment using Advanced SQL Techniques and Python-based visualization to uncover insights on sales trends, customer segmentation, shipping cost optimization, and payment preferences.

Test repo for the Smartboard project

Identify customer segments using unsupervised ML

Machine Learning Engineer Nanodegree, Unsupervised Learning, Creating Customer Segments

Customers RFM Clustering (Market Segmentation based on Behavioral Approach)

Identifying customer segments based on their purchasing behavior using RFM analysis and K-Means clustering.

Regression , Classification and Segmentation projects

I worked on a data set to find the groups of people who have some kind of pattern. we used k-means clustering to find the pattern based on parameters available in the dataset.

A topic designed by Warwick Business School requires students to enhance loan portfolio management by utilising cluster analysis to group borrowers with similar characteristics, enabling personalised loan products, targeted marketing strategies, and a better customer support process to serve the unique needs of each segment through cluster analysis

Project - Creating customer segments | Unsupervised learning | Python | PCA | Gaussian Mixture Model

Project explores the transaction history of an online household goods store through detailed data analysis, visualizations, and statistical hypothesis testing, offering valuable insights into purchase trends, customer behavior, and strategic product decisions.