This project demonstrates how to train a simple perceptron to replicate the logic of an AND gate using Python 3.9.19, numpy and matplotlib. The notebook walks through data preparation, model definition, training, and visualization.
.gitignore: This file prevents temporary files, Python cache files, environment folders (venv), and other system-generated files from being included in your Git repository.Basic_Perceptron_AND_Exercise.ipynb: The main notebook that contains all code for defining, training, and visualizing the perceptron.LICENSE: Provides the legal terms under which your code can be used, modified, and distributed.README.md: Overview of the project, its purpose, and how to use it.requirements.txt: List of Python dependencies to install for running the notebook.
This project requires basic knowledge of:
- Machine Learning (Perceptron basics)
- Python programming
- Jupyter Notebook
- Clone the repository:
git clone https://github.com/lfelipecas/perceptron-AND-gate-project
- Install the dependencies:
pip install -r requirements.txt
- Launch Jupyter Notebook and open
Basic_Perceptron_AND_Exercise.ipynb:
- L. Felipe Castañeda G.
This project is licensed under the MIT License - see the LICENSE file for details.