Project: Creating Customer Segments using Unsupervised Learning
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Updated
Jan 18, 2017 - Jupyter Notebook
Project: Creating Customer Segments using Unsupervised Learning
Udacity Machine Learning Engineer Nanodegree Unsupervised Learning Project: Creating Customer Segments
Creating Customer Segments for Udacity Machine Learning Engineer Nanodegree
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.
Projects of Udacity's Machine Learning Specialization Nanodegree program.
Project done in ML course
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…
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…
Customer Segments - Machine Learning Nanodegree from Udacity
My final submitted project for udacity basic ML course, customer segments
Machine Learning Engineer Nanodegree, Unsupervised Learning, Creating Customer Segments
This project uses unsupervised learning techniques and decomposition methods to find meaningful structure in the data.
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 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.
We apply PCA transformations to the data and implement clustering algorithms to segment the transformed customer data
Code to perform clustering using self organizing maps on retail customer data.
Customer Segmentation using Clustering (Machine Learning)
Applied Unsupervised Learning techniques on product spending data collected for customers of a wholesale distributor to identify customer segments hidden in the data.
These are all the assignments from Udacity Nanodegree Machine Learning course
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