In this project I will apply unsupervised learning techniques to 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 that I will use has been provided by Arvato Analytics, and represents a real-life data science task.
First of all you need to have jupyter notebook installed. You can find the installation documentation for the Jupyter platform, on ReadTheDocs. The documentation for advanced usage of Jupyter notebook can be found here.
For a local installation, make sure you have pip installed and run:
$ pip install notebook
Then you can open the notebook with the following command:
$ jupyter notebook
Finally you have to choose 'Identify_Customer_Segments.ipynb'.
Alternatively you can open up 'Identify_Customer_Segments.html' with your favourite browser.
This is the last project of the Udacity Machine Learning Nanodegree. The template of the notebook was given, but most of the code and the answers were written by myself.