This Flask-based web application predicts travel budgets based on user input and suggests destinations within the predicted budget. Users can register, log in, provide travel information, and receive budget predictions.

• Prerequisites
• Installation
• Usage
• Project Structure
• Dependencies
• Contributing

• Python 3.x
• SQLite (for the included database)
• pip package manager

1. Clone the repository:

   git clone https://github.com/sangitaa11/Geovoyage-Effortles_Travel_budget_exploration.git
   cd travel-budget-app

2. Create a virtual environment (optional but recommended):

   python -m venv venv

3. Activate the virtual environment:

   • On Windows:

     venv\Scripts\activate

   • On macOS and Linux:

     source venv/bin/activate

4. Install dependencies:

   pip install -r requirements.txt

1. Run the application:

   python app.py

2. Open your web browser and navigate to https://127.0.0.1:5000/

3. Explore the different features of the application, such as user registration, budget prediction, and destination suggestions.

• app.py: The main Flask application file.
• templates/: HTML templates for rendering web pages.
• trained_model.joblib: The pre-trained machine learning model for budget prediction.
• preprocessed_travel.csv: Preprocessed travel data used by the model.
• site.db: SQAlchemy database file for user information.

• Flask
• Flask-SQLAlchemy
• Flask-Login
• Flask-Bcrypt
• scikit-learn
• pandas
• numpy

1. Fork the repository.
2. Create a new branch: git checkout -b feature-name.
3. Commit your changes: git commit -m 'Add feature'.
4. Push to the branch: git push origin feature-name.
5. Submit a pull request.