This project is an implementation of a neural network with multiple hidden layers. It is designed to perform forward and backward propagation, allowing you to compute and analyze the output of a neural network.
The purpose of this project is to demonstrate a basic neural network implementation and provide a starting point for further exploration and development of neural network models. You can use this code to understand the inner workings of a neural network, modify it for specific applications, or use it as a learning resource.
- C++ compiler (e.g., g++)
- Linux operating system (for
forkandpipefunctions)
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Clone the repository to your local machine:
git clone https://github.com/yourusername/neural-network-project.git
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Compile the code using the C++ compiler:
g++ main.cpp -o neural_network
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Run the executable:
./neural_network
main.cpp: The main source file containing the neural network implementation.file.txt: A configuration file used for input data.
The code simulates a neural network with multiple hidden layers. It performs forward propagation and computes the output of the neural network. You can review the code in main.cpp to understand the implementation details.