Use k-means clustering to segment credit card customer data from a Kaggle dataset

Perform customer segmentation using KMeans and market basket analysis using Apriori.

Analyze demographics data for customers of a mail-order sales company in Germany.

Customer Segmentation using KMeans.

Customer segmentation on data online retail 2009-2011

Segmenting customers of an audiobook platform and predicting their future purchase.

It is highly related to the Customer Segmentation problem, so with RFM Analysis itself as well

Course of business intelligence bootcamp by Dibimbing

PySpark data analysis of the Online Retail Data Set

Hey there! 👋 This is my little machine learning playground on GitHub. You'll find Kaggle projects here, solving all kinds of fun problems - predicting sales, figuring out good wine, you name it. All using a cocktail of ML models. Explore, learn, or just enjoy the data-driven ride. Happy coding! 🚀

KPMG-Virtual-Internship: This repo contains all the solutions and resources for the data analytics virtual internship provided by KPMG via Forage

This repository contains a customer segmentation project implemented in a Jupyter Notebook using Python. Customer segmentation is a crucial strategy for businesses aiming to understand their customer base better, enabling targeted marketing strategies and personalized customer experiences.

This repository showcases my project completed during the KPMG AU Virtual Internship by Forage. I had the opportunity to take the mystery out of big data and learn what it's like to produce business results with the KPMG data analytics team. I am excited to share my learnings and the outcomes of this enriching internship.

Predict customer churn through supervised and unsupervised techniques, perform feature engineering, incorporate network science. The project also covers extensive data preprocessing, making informed churn assumptions and exploratory data analysis.

Can we do Customers Segmentation using PHP and Unsupervized Machine Learning ? Yes we can ! 🤡

The repo focuses on my works in data science

This was done as a part of Springboard Data Science Career Track course (Unit10.5.4. Customer Segmentation Using Clustering).

Capstone project for the Udacity MLND on the prediction of customer acquisition based on regional demographics and customer attributes. With the help of supervised and unsupervised learning techniques.

Customer Segmentation Analysis, developed using Python, by using Clustering Algorithm for the purpose of dividing the customers into groups based on the similarity in different ways that are relevant to marketing such as location, items, spending score, salary and accordingly identify customers’ behavior and interests and focus on them for futur…

Customer segmentation model - RFM framework