Project: Creating Customer Segments using Unsupervised Learning

This project uses unsupervised learning techniques and decomposition methods to find meaningful structure in the data.

RFM (Recency, Frequency, Monetary) analysis is a proven marketing model for behavior based customer segmentation. It groups customers based on their transaction history – how recently, how often and how much did they buy. RFM helps divide customers into various categories or clusters to identify customers who are more likely to respond to promot…

Project done in ML course

A curated list of awesome customer analytics content

Reviewed unstructured data to understand the patterns and natural categories that the data fits into. Made predictions about the natural categories of multiple types in a dataset, then checked these predictions against the result of unsupervised analysis.

Code to perform clustering using self organizing maps on retail customer data.

Udacity Machine Learning Engineer Nanodegree Unsupervised Learning Project: Creating Customer Segments

This repo contains unsupervised models including the Latent Dirichlet Allocation (LDA) model applied to a corpus of research papers and a clustering analysis applied to customer segmentation.

In this project, I will analyze a dataset containing data on various customers' annual spending amounts (reported in monetary units) of diverse product categories for internal structure. One goal of this project is to best describe the variation in the different types of customers that a wholesale distributor interacts with. Doing so would equip…

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

Customer Segments - Machine Learning Nanodegree from Udacity

Projects of Udacity's Machine Learning Specialization Nanodegree program.

Machine Learning Engineer Nanodegree, Unsupervised Learning, Creating Customer Segments

This project is based on Unsupervised Learning

We apply PCA transformations to the data and implement clustering algorithms to segment the transformed customer data

Creating Customer Segments for Udacity Machine Learning Engineer Nanodegree

Customer Segmentation Anaylsis

This project identify segments of the population that form the core customer base for a mail-order sales company in Germany. These segments can then be used to direct marketing campaigns towards audiences that will have the highest expected rate of returns. The data has been provided by Bertelsmann Arvato Analytics.