Neural Network Project

Overview

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.

Purpose

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.

Getting Started

Prerequisites

• C++ compiler (e.g., g++)
• Linux operating system (for fork and pipe functions)

Installation

1. Clone the repository to your local machine:

   git clone https://github.com/yourusername/neural-network-project.git
   

2. Compile the code using the C++ compiler:

   g++ main.cpp -o neural_network
   

3. Run the executable:

   ./neural_network
   

Project Structure

• main.cpp: The main source file containing the neural network implementation.
• file.txt: A configuration file used for input data.

Usage

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.