https://github.com/cyprianfusi/credit-card-customer-segmentation-using-k-means-algorithm
You are a data scientist working for a credit card company. You're asked to help segment a dataset containing information about the company’s clients into different groups to enable the company to apply different business strategies for each type of customer.
https://github.com/cyprianfusi/credit-card-customer-segmentation-using-k-means-algorithm
customer-segmentation kmeans-clustering pandas-python unsupervised-machine-learning
Last synced: 9 months ago
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You are a data scientist working for a credit card company. You're asked to help segment a dataset containing information about the company’s clients into different groups to enable the company to apply different business strategies for each type of customer.
- Host: GitHub
- URL: https://github.com/cyprianfusi/credit-card-customer-segmentation-using-k-means-algorithm
- Owner: CyprianFusi
- Created: 2024-07-18T05:52:14.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-26T13:10:57.000Z (10 months ago)
- Last Synced: 2025-02-26T14:24:20.552Z (10 months ago)
- Topics: customer-segmentation, kmeans-clustering, pandas-python, unsupervised-machine-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 2.71 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Credit-Card-Customer-Segmentation-using-k-means-Algorithm
## The Scenario
You are a data scientist working for a credit card company. You're asked to help segment a dataset containing information about the company’s clients
into different groups to enable the company to apply different business strategies for each type of customer.
## The Dataset
The dataset is named [customer segmentation](https://www.kaggle.com/datasets/yasserh/customer-segmentation-dataset) and it can be downloaded from Kaggle. We have been told that the data engineering team has already cleaned most of the data so we can focus on building the best possible model to segment the data. Also, in a planning meeting with the Data Science coordinator, it was decided that we should use the **`K-means`** algorithm to segment the data.
**It's worth noting that `k.means` is an `unsupervised` machine learning algorithm. In `segmentation` or `clustering`, all the columns are considered as features and there is no such thing as target.**