techinAI/customer_segments

Segmentation and Clustering to find patterns and structures in unlabeled data, perform feature transformations and improve the predictive performance of your models.

Project 3: Unsupervised Learning

Creating Customer Segments

Install

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

• NumPy
• Pandas
• matplotlib
• scikit-learn

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

Udacity recommends our students install Anaconda, i pre-packaged Python distribution that contains all of the necessary libraries and software for this project.

Code

Template code is provided in the notebook customer_segments.ipynb notebook file. Additional supporting code can be found in renders.py. While some code has already been implemented to get you started, you will need to implement additional functionality when requested to successfully complete the project.

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 ipy

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.