# Neural Net

## Overview

`neural_net` is a personal learning project focused on implementing a basic neural network from scratch using C++. The goal of this project is to gain a deep understanding of neural network architecture, training algorithms, and fundamental machine learning concepts.

## Features

- Custom neural network implementation in C++
- Support for basic feed-forward neural network architecture
- Configurable number of layers and neurons
- Implementation of key activation functions
- Simple data loading and preprocessing utilities
- Basic performance metrics and evaluation

## Prerequisites

- C++17 or later
- CMake (version 3.10 or higher)
- A modern C++ compiler (GCC, Clang, or MSVC)

## Installation

1. Clone the repository:
   ```bash
   git clone https://github.com/aselimov/neural_net.git
   cd neural_net
   ```

2. Create a build directory and compile:
   ```bash
   mkdir build
   cd build
   cmake ..
   make
   ```

## Learning Objectives

- Understand neural network architecture
- Implement core machine learning algorithms
- Practice advanced C++ programming techniques
- Explore computational efficiency in ML implementations

## Roadmap

- [x] Activation functions
- [ ] Basic neural network structure
- [ ] Backpropagation algorithm
- [ ] Regularization techniques
- [ ] Performance optimizations

## License

This project is [MIT](LICENSE) licensed.

## Contact

Alex Selimov  - [alex@alexselimov.com](mailto:alex@alexselimov.com)