MariaLuizaCw / intel-comp

Repository for storing the practical work of the Computational Intelligence course at PESC UFRJ (CPS844)

Computational Intelligence

This repository contains the code and notebooks developed for the practical work of Computational Intelligence. The project was implemented using Python and Jupyter Notebooks.

Repository Structure

• module.py: This file contains the auxiliary functions needed to develop each of the experiments, including:

  • Functions that implement the algorithms.
  • Functions that generate data.
  • Functions that calculate the error.
  • Functions that represent the target.

• Notebooks:

  • perceptron.ipynb: Contains the implementation and experiments with the Perceptron algorithm.
  • regression_linear.ipynb: Contains the implementation and experiments with the Linear Regression algorithm.
  • regression_nonlinear.ipynb: Contains the implementation and experiments with Nonlinear Data and tranformations.
  • pocket_pla.ipynb: Contains the implementation and experiments with the Pocket PLA (Perceptron Learning Algorithm).

Requirements

To run the notebooks, make sure you have the following Python packages installed:

• NumPy
• Matplotlib
• Jupyter

You can install these packages using pip:

pip install numpy pandas matplotlib jupyter

How to Run

1. Clone this repository:

git clone https://github.com/username/repository.git

2. Navigate to the repository directory:

cd repository

3. Start Jupyter Notebook:

jupyter notebook

4. Open one of the notebooks (perceptron.ipynb, regression_linear.ipynb, regression_nonlinear.ipynb, or pocket_pla.ipynb) and run the cells to view the experiments and results.

Contribution

Contributions are welcome! If you have suggestions or improvements, please open an issue or submit a pull request.

Acknowledgements

Special thanks to Professor Pedreira and the TA Vinicius Costa for their support and guidance throughout this project.

License

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