https://github.com/ludreinsalvador/churn-prediction
This aims to predict customer churn based on the lack of transactions over the past 3 months. It uses behavioral features such as member_id, quantity, transaction_date, and category_name to identify customers who are at risk of churning. It focuses on transaction behavior prior to churn to create accurate predictions.
https://github.com/ludreinsalvador/churn-prediction
churn-analysis colab-notebook customer-churn-prediction jupyter-notebooks machine-learning
Last synced: 8 months ago
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This aims to predict customer churn based on the lack of transactions over the past 3 months. It uses behavioral features such as member_id, quantity, transaction_date, and category_name to identify customers who are at risk of churning. It focuses on transaction behavior prior to churn to create accurate predictions.
- Host: GitHub
- URL: https://github.com/ludreinsalvador/churn-prediction
- Owner: ludreinsalvador
- Created: 2025-01-18T07:23:49.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2025-02-16T15:02:37.000Z (8 months ago)
- Last Synced: 2025-02-16T15:37:23.608Z (8 months ago)
- Topics: churn-analysis, colab-notebook, customer-churn-prediction, jupyter-notebooks, machine-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 14.9 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Churn Prediction (Machine Learning)
**Instructor:** Mr. Lorenzo Sta. Maria, Data Scientist at Globe Telecom
---
## Overview
This repository aims to predict customer churn based on the lack of transactions over the past 3 months. It uses behavioral features such as **member_id**, **quantity**, **transaction_date**, and **category_name** to identify customers who are at risk of churning. It focuses on transaction behavior prior to churn to create accurate predictions.
---
## Data Used
- **[Data Folder](/data/)** - This contains datasets relevant for churn prediction analysis.
- **[week2_for_teacher_demo.csv.gz](/data/week2_for_teacher_demo.csv.gz)** - This is a sample dataset for churn prediction.
---
## Notebooks
- **[Notebooks Folder](/notebooks/)** - This contains Jupyter notebooks for data analysis and model building.
- **[salvador_week2.ipynb](/notebooks/salvador_week2.ipynb)**: Business & Data Understanding
- **[salvador_week3.ipynb](/notebooks/salvador_week3.ipynb)**: Data Engineering
- **[salvador_week4.ipynb](/notebooks/salvador_week4.ipynb)**: Machine Learning Model Engineering
- **[salvador_week5.ipynb](/notebooks/salvador_week5.ipynb)**: ML Model Evaluation
- **[salvador_week6.ipynb](/notebooks/salvador_week6.ipynb)**: Model Deployment