Neural Network Implementation Using Eigen3 Library
This project implements a neural network from scratch in C++ using the Eigen3 library for efficient linear algebra operations. It includes functionalities for forward propagation, backpropagation, and training with synthetic data.
For a more comprehensive understanding of the neural network and its components, please refer to the following files within this repository:
- HowItWorks.md: Detailed explanation of the core functions and their roles within the neural network.
- IntroToNeuralNetworks.md: Introduction to neural networks, covering the mathematical concepts and code implementation in an accessible manner.
- Eigen3: C++ template library for linear algebra.
To build and run this project, follow these steps:
- Clone the repository:
git clone <repository-url> cd NeuralNetwork
- Create a build directory and navigate to it:
mkdir build cd build - Run CMake and build the project
cmake .. make
- Execute the compiled program
./NeuralNetwork
This project is licensed under the GPL-3.0 License. See the LICENSE file for details.
For issues or questions regarding this project, please open an issue on the GitHub repository.
This README.md file provides an overview of the project, instructions for building and running it, usage examples, key features, contribution guidelines, licensing information, and contact details. Adjust the content as needed to suit your project specifics and preferences.