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docs: Update Project Description in README
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lmego authored Feb 9, 2017
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### Project Description

This is the 4th project for the Machine Learning Engineer Nanodegree. In this project I apply unsupervised learning techniques on product spending data collected for customers of a wholesale distributor to identify customer segments hidden in the data. I first explore the data by selecting a small subset to sample and determine if any product categories highly correlate with one another. Afterwards, you I preprocess the data by scaling each product category and then identifying (and removing) unwanted outliers. Then I apply PCA transformations to the data and implement a clustering algorithm (Gaussian Mixture Model)to segment the transformed customer data. Finally, I compare the segmentation found with an additional labeling and consider ways this information could assist the wholesale distributor with future service changes.
This is the 4th project for the Machine Learning Engineer Nanodegree. In this project I apply unsupervised learning techniques on product spending data collected for customers of a wholesale distributor to identify customer segments hidden in the data.

Here, I first explore the data to determine if any product categories highly correlate with one another by observing a small subset of the data and also by ploting a scater matrix. Afterwards, I preprocess the data by scaling each product category and then identifying (and removing) unwanted outliers. Then I apply PCA transformations to the data and implement a clustering algorithm (Gaussian Mixture Model)to segment the transformed customer data. Finally, I compare the segmentation found with an additional labeling and consider ways this information could assist the wholesale distributor with future service changes.

### Install

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