Customer Segment Identification

Unsupervied learning algorithms have been used to classify various customers of a company into clusters.

About the dataset

The dataset used is from UCI ML repository

Attribute Information:

1. FRESH: annual spending (m.u.) on fresh products (Continuous);
2. MILK: annual spending (m.u.) on milk products (Continuous);
3. GROCERY: annual spending (m.u.)on grocery products (Continuous);
4. FROZEN: annual spending (m.u.)on frozen products (Continuous)
5. DETERGENTS_PAPER: annual spending (m.u.) on detergents and paper products (Continuous)
6. DELICATESSEN: annual spending (m.u.)on and delicatessen products (Continuous);
7. CHANNEL: customers’ Channel - Horeca (Hotel/Restaurant/Café) or Retail channel (Nominal)
8. REGION: customers’ Region – Lisnon, Oporto or Other (Nominal)

Aditional information about the dataset can be found on the link above.

Software and Libraries

This project uses the following software and Python libraries:

• [Python 2.7]
• [NumPy]
• [pandas]
• [scikit-learn]
• [matplotlib]

You will also need to have software installed to run and execute a [Jupyter Notebook]