Using unsupervised learning methods to help business better understand customers

Customer segmentation using k-modes unsupervised clustering

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

Simple example code to show how to do customer segmentation. Enjoy it!

Predicting Convenience Store Shrink

Muticlass classification problem to classify customer segments by different chemical properties of wine.

Analysing the content of an E-commerce database that contains list of purchases. Based on the analysis, I develop a model that allows to anticipate the purchases that will be made by a new customer, during the following year from its first purchase.

In this project I apply unsupervised learning techniques and principal components analysis on product spending data collected for customers of a wholesale distributor in Lisbon, Portugal to identify customer segments hidden in the data.

By means of this project I am trying to create a value-based customer segmentation model using RFM(Recency, Frequency, Monetary) analysis in python using pandas, numpy and matplotlib

Showcase for using H2O and R for scoring for marketing campaign in retail

generalized code used in my master thesis

The repository contains various Machine Learning based solutions for data analysis, regression and clustering problems

Udacity Data Science Nanodegree program, unsupervised learning, identify customers segments

Console crawlers can help in many fundamental processes. Like: Person Dataset, Customer review, Statistics exactness, and Market research.

EDA and customer segmentation with RFM analysis on hacker earth dataset. https://www.hackerearth.com/challenge/hiring/LMG-analytics-data-science-hiring-challenge

Cluster Big Bazaar customers based on their shopping and other data given using K-Means and Hierarchical Clustering.

Machine Learning Engineer Nanodegree, Unsupervised Learning, Creating Customer Segments

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