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Optimized wholesale distributor’s delivery service by classifying their customers into segments given their annual spending amounts of diverse product categories. Python.

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Creating Customer Segments

Unsupervised Learning

Install

This project requires Python 2.7 and the following Python libraries installed:

You will also need to have software installed to run and execute an iPython Notebook

It is recommended to install Anaconda, a pre-packaged Python distribution that contains all of the necessary libraries and software for this project.

Code

Source code is in the notebook customer_segments.ipynb notebook file.

Run

In a terminal or command window, navigate to the top-level project directory creating_customer_segments/ (that contains this README) and run one of the following commands:

ipython notebook customer_segments.ipynb jupyter notebook customer_segments.ipynb

This will open the iPython Notebook software and project file in your browser.

Data

The dataset used in this project is included as customers.csv. You can find more information on this dataset on the UCI Machine Learning Repository page.

Creating-Customer-Segments

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Optimized wholesale distributor’s delivery service by classifying their customers into segments given their annual spending amounts of diverse product categories. Python.

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