https://github.com/bhaveshbhakta/hotel-booking-prediction-using-ann
Hotel Booking Prediction
https://github.com/bhaveshbhakta/hotel-booking-prediction-using-ann
ann artificial-neural-networks data-visualization deep-learning hotel-booking
Last synced: 8 months ago
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Hotel Booking Prediction
- Host: GitHub
- URL: https://github.com/bhaveshbhakta/hotel-booking-prediction-using-ann
- Owner: BhaveshBhakta
- Created: 2024-12-29T11:24:53.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-01-26T11:18:51.000Z (9 months ago)
- Last Synced: 2025-01-26T12:21:01.564Z (9 months ago)
- Topics: ann, artificial-neural-networks, data-visualization, deep-learning, hotel-booking
- Language: Jupyter Notebook
- Homepage:
- Size: 1.99 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Hotel Booking Prediction
## Project Overview
This project explores and analyzes hotel booking data to identify trends, patterns, and insights related to customer behavior, booking cancellations, market segments, and seasonal price variations. Using a combination of exploratory data analysis and visualization techniques, the project provides a comprehensive understanding of factors influencing hotel bookings and cancellations.
## Key Features
- **Data Analysis**: Detailed analysis of over 119,000 records of hotel bookings, including variables such as lead time, customer type, and booking status.
- **Visualizations**: Rich visualizations such as distribution plots, scatter plots, and choropleth maps to present insights.
- **Cancellation Insights**: Analysis of cancellation trends and factors influencing cancellations.
- **Seasonal Trends**: Examination of price variations for different hotel types over months.
- **Market Segment Insights**: Breakdown of bookings across market segments and distribution channels.
- **Geographical Analysis**: Mapping guest distributions across countries.
## Purpose and Applications
The purpose of this project is to provide actionable insights for hotel managers, marketers, and data analysts by leveraging historical data to:
- Improve operational efficiency by understanding booking patterns.
- Identify factors leading to cancellations and devise strategies to reduce them.
- Optimize pricing strategies based on seasonal trends and market demands.
- Enhance customer segmentation and targeted marketing.
- Inform decision-making through data-driven insights.
## Installation
1. Clone the repository:
```bash
git clone https://github.com/BhaveshBhakta/Hotel-Booking-Prediction-Using-ANN.git
```
2. Navigate to the project folder:
```bash
cd Hotel-Booking-Prediction-Using-ANN
```
3. Run the notebook
## Collaboration
Contributions are welcome! Feel free to fork the repository, make improvements, and submit a pull request.