This project is a basic implementation of a feed-forward neural network using the C language and graph theory. The main goal is to learn how these models work by building one from scratch. Note that the comments I write on my code are probably more complete and descriptive than this README.
- Feed Forward Architecture: Data flows from input to output (still in progress).
- Graph Representation: Uses adjacency matrices to represent node connections.
- Activation Functions: Includes basic activation functions (like Sigmoid).
This project is part of my learning journey with C programming and neural networks. The code is still under development and might not follow best practices.
Feedback and suggestions are welcome!
This project is licensed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). This means others can share and adapt the code for non-commercial purposes, as long as credit is given to the original author. For more details, see the LICENSE file.