ananttripathi/Tourism_Project

End-to-end MLOps pipeline for predicting customer purchase of a wellness tourism package. Includes data registration on Hugging Face, XGBoost model training with MLflow tracking, CI/CD using GitHub Actions, Dockerized Streamlit app, and deployment to Hugging Face Spaces.

36
/ 100
Emerging

This project helps travel companies predict which customers are most likely to purchase a wellness tourism package. You input customer demographic and interaction data, and it outputs a prediction (purchase or no purchase) along with a confidence score. This tool is for sales managers, marketing analysts, or strategists at travel agencies who want to identify high-potential leads.

Use this if you need a reliable way to score potential customers on their likelihood to buy specific travel packages, helping your sales team focus their efforts.

Not ideal if you're looking for a simple, one-off analysis; this project is designed for continuous use and integration into an operational workflow.

tourism travel-sales customer-prediction lead-scoring marketing-analytics
No Package No Dependents
Maintenance 10 / 25
Adoption 4 / 25
Maturity 13 / 25
Community 9 / 25

How are scores calculated?

Stars

7

Forks

1

Language

Python

License

MIT

Last pushed

Jan 25, 2026

Commits (30d)

0

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