https://github.com/nazanin1369/creating_customer_segments
Applying unsupervised learning techniques on product spending data collected for customers of a wholesale distributor in Lisbon, Portugal to identify customer segments hidden in the data
https://github.com/nazanin1369/creating_customer_segments
machine-learning unsupervised-learning
Last synced: 8 months ago
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Applying unsupervised learning techniques on product spending data collected for customers of a wholesale distributor in Lisbon, Portugal to identify customer segments hidden in the data
- Host: GitHub
- URL: https://github.com/nazanin1369/creating_customer_segments
- Owner: Nazanin1369
- Created: 2016-11-05T22:15:31.000Z (almost 9 years ago)
- Default Branch: gh-pages
- Last Pushed: 2016-11-13T07:16:29.000Z (almost 9 years ago)
- Last Synced: 2025-01-07T20:49:55.144Z (9 months ago)
- Topics: machine-learning, unsupervised-learning
- Language: HTML
- Size: 1.87 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
## Unsupervised Learning: Creating Customer Segments
### [Click to view online](https://nazanin1369.github.io/creating_customer_segments/)
### How to Install
This project requires **Python 2.7** and the following Python libraries installed:
- [NumPy](http://www.numpy.org/)
- [Pandas](http://pandas.pydata.org)
- [matplotlib](http://matplotlib.org/)
- [scikit-learn](http://scikit-learn.org/stable/)
You will also need to have software installed to run and execute an [iPython Notebook](http://ipython.org/notebook.html)
Udacity recommends our students install [Anaconda](https://www.continuum.io/downloads), 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```
```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](https://archive.ics.uci.edu/ml/datasets/Wholesale+customers) page.