This project explores various unsupervised learning techniques such as clustering and principal component analysis(PCA) to segment a wholesaler's various customers. This dataset comes from UCI Machine Learning Repository. A subset of the data has been used for this project and can be found in the customers.csv file.
This project is using Python 2.7 and needs the following libraries:
- numpy
- pandas
- scikit-learn
- matplotlib
- jupyter notebook
These can be installed using pip or conda if using Anaconda.
The project is implemented in a Jupyter notebook and can be run using the following from a terminal:
jupyter notebook customer_segments.ipynb