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Location Prediction App

Dragon04

Project link =>https://dragon04.streamlit.app/

Project Description

The Location Prediction App is a web application built with Streamlit and Folium that visualizes geographic coordinates and provides predictive modeling for location-based data. The app allows users to click on a world map to select a location, and then uses a machine learning model to predict and display nearby locations based on the selected coordinates.

Features

  • Interactive map rendering using Folium.
  • Clickable map to select a location.
  • Predictive modeling using LightGBM for latitude and longitude predictions.
  • Visualization of model outputs on the map.

Installation

To run this project locally, you'll need to set up your environment and install the necessary dependencies. Follow these steps:

  1. Clone the repository:

    git clone https://github.com/your-username/location-prediction-app.git
cd location-prediction-app

  2. Set up a virtual environment (optional but recommended):

    python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

  3. Install the required packages:

    pip install -r requirements.txt

  4. Prepare your data:

    Ensure that you have the new.csv data file in the same directory as the script. This file should contain latitude and longitude columns along with other features used for prediction.

Usage

  1. Run the Streamlit app:

    streamlit run app.py

  2. Access the app:

    Open your web browser and navigate to local host.

  3. Interact with the app:

    • Click on the map to select a location.
    • The app will display the coordinates of the clicked location.
    • The model will predict nearby locations and update the map with the predicted points.

Code Structure

  • app.py: Main Streamlit application script.
  • new.csv: Data file used for training the machine learning model.
  • requirements.txt: List of Python packages required for the project.
  • model_latitude.txt and model_longitude.txt: Saved LightGBM models for latitude and longitude predictions.

Requirements

The project requires the following Python packages:

  • pandas
  • numpy
  • math
  • lightgbm
  • scikit-learn
  • streamlit
  • folium
  • streamlit_folium

These packages are listed in the requirements.txt file.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements

  • Streamlit - For providing a powerful tool to build interactive web applications.
  • Folium - For creating interactive maps.
  • LightGBM - For the gradient boosting framework used for predictive modeling.

Contact

For any questions or issues, please open an issue on this repository or contact me at [[email protected]].