Web Links Classification with Machine Learning

This project aims to classify different web links into different categories using machine learning. The project is built by combining frontend, backend, and machine learning components.

Installation and Execution

To run this project, follow the steps below:

1. Clone the repository using the following command:

git clone https://github.com/DanielaGomez98/FinalProject-AI.git

2. Once the repository is cloned, navigate to the project folder:

cd FinalProject-AI

3. Create a virtual environment and install the project dependencies using Poetry:

poetry shell
poetry install

4. Run the project using Docker Compose:

docker-compose up

With these steps, you should be able to run the project on your local machine.

** The Machine Learning model can be found at the following path: https://uao-my.sharepoint.com/:f:/g/personal/daniela_gomez_ayalde_uao_edu_co/EtNWEM9hVO5PrxUB_rPHB3MBV00lW8nbdqO9CHpi5p2EDA?e=URtUHu.

It must be downloaded and inserted in the folder "backend/models/sklearn".

Contributing

If you would like to contribute to this project, follow the steps below:

1. Fork the repository on GitHub.
2. Clone your forked repository to your local machine.
3. Create a branch for your new feature or problem solution.
4. Make your changes on your branch.
5. Push your branch to your forked repository on GitHub.
6. Create a pull request from your branch on your forked repository to the main branch of the original repository.

Credits

This project was created by Daniela Gómez, Roberto Guerrero and Manuel Henao.