https://github.com/burcuyesilyurt/teco_customer_segmentation
Develop Machine Learning model to predict customer churn.
https://github.com/burcuyesilyurt/teco_customer_segmentation
customer-segmentation machine-learning prediction python supervised-machine-learning
Last synced: 2 months ago
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Develop Machine Learning model to predict customer churn.
- Host: GitHub
- URL: https://github.com/burcuyesilyurt/teco_customer_segmentation
- Owner: burcuyesilyurt
- Created: 2024-08-14T18:36:26.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-08-14T19:20:17.000Z (almost 2 years ago)
- Last Synced: 2025-08-04T20:20:01.004Z (12 months ago)
- Topics: customer-segmentation, machine-learning, prediction, python, supervised-machine-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 1.38 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Description:
For this task, I will develop a machine learning model to predict customer churn, a common business problem. Customer churn prediction is crucial for businesses as it helps in identifying customers who are likely to stop using a service or product, allowing the company to take proactive steps to retain them.
## Dataset Selection
I'll use the popular "Telco Customer Churn" dataset, which contains information about customers of a telecom company. The dataset includes various features such as customer demographics, account information, and services used, as well as a label indicating whether the customer churned or not.
## Problem Definition
The problem is a binary classification task, where the goal is to predict whether a customer will churn (1) or not churn (0) based on the features provided in the dataset.
## Challenges:
Handling class imbalance if the dataset has more non-churned customers than churned ones.
Avoiding overfitting.