These are all the assignments from Udacity Nanodegree Machine Learning course

Customer Segmentation using Clustering (Machine Learning)

In this project, you will work with real-life data provided to us by our Bertelsmann partners AZ Direct and Arvato Finance Solution. The data here concerns a company that performs mail-order sales in Germany. Their main question of interest is to identify facets of the population that are most likely to be purchasers of their products for a mail…

Customer segmentation is a process where we divide the consumer base of the company into subgroups. We need to generate the subgroups by using some specific characteristics so that the company sells more products with less marketing expenditure.

Basic RFM model to kickstart customer value segmentation. This project aims to guide the first time user to have a bouncing board into setting up their first segmentation model.

This repository contains RFM analysis applied to identify customer segments for global retail company and to understand how those groups differ from each other.

My final submitted project for udacity basic ML course, customer segments

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.

Customer Segmentation Anaylsis

Creating Customer Segments for Udacity Machine Learning Engineer Nanodegree

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

This project is based on Unsupervised Learning

Machine Learning Engineer Nanodegree, Unsupervised Learning, Creating Customer Segments

Projects of Udacity's Machine Learning Specialization Nanodegree program.

Customer Segments - Machine Learning Nanodegree from Udacity

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

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…

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.

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