Add hotel stay cost forecasting example using Prophet

[akhil0404-tech]

Summary

This PR introduces a real-world forecasting example that predicts hotel stay costs using the Prophet library. The example includes a notebook with seasonal effects, holiday regressors, and evaluation metrics, along with interactivity via ipywidgets.

Files Added

• examples/HotelStayCostForecasting/notebook.ipynb: Full forecasting workflow
• examples/HotelStayCostForecasting/README.md: Overview and setup
• examples/HotelStayCostForecasting/hotel_stay_costs.csv: Example dataset
• examples/HotelStayCostForecasting/visuals/: Visual output

Features Demonstrated

• Time series forecasting with custom regressors (seasons)
• Holiday impacts added to improve accuracy
• Evaluation with MAE, RMSE, and R²
• Slider-based interactive forecast preview
• Saved model artifact (prophet_model.pkl)

Why It’s Useful

This example adds a real-world use case (hospitality sector) to Prophet’s examples. It can help users understand how to apply Prophet to pricing, logistics, and demand forecasting problems.

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Author: Akhil Chatla
LinkedIn: https://www.linkedin.com/in/akhil-chatla-07847b1a7

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[akhil0404-tech]

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[akhil0404-tech]

Hi @facebook/prophet-maintainers ,

I’ve completed the CLA and submitted a new forecasting example for hotel stay cost prediction using Prophet (PR #2666). Would love your review whenever you get a chance. Really excited to contribute to this amazing project! : )

Thanks a lot in advance!