Neural-Network-Scratch

A neural network implementation from scratch using Rust. This project demonstrates the fundamentals of neural networks, including feedforward and backpropagation, along with essential matrix operations.

Features

• Feedforward Neural Network: Process inputs through multiple layers to produce outputs.
• Backpropagation: Implemented to adjust weights based on the error of the output.
• Activation Functions: Includes popular activation function as Sigmoid.
• Matrix Operations: Basic operations such as addition, subtraction, multiplication, transpose, and dot multiplication.

Getting Started

Prerequisites

Make sure you have Rust installed on your machine. You can install it from rust-lang.org.

Installation

Clone the repository:

git clone https://github.com/NithinKonda/neural-network-scratch.git
cd rust-neural-network

Running the Project To run the project, use the following command:

cargo run