Neural-Nets-C

This repository contains implementations and experiments with neural networks in C, focusing on educational purposes. The project demonstrates fundamental concepts of neural networks through a modular codebase that includes linear algebra utilities.

Features

• Supports multiple neural network architectures, including feedforward and deep neural networks.
• Supports different optimizers (SGD, Momentum, Adam).
• Offers several activation functions (ReLU, Sigmoid, TanH).
• Includes loss functions and regularization techniques.
• Linear algebra utilities for matrix and vector operations.

Linear Algebra Functions

The lin_alg.h header file provides essential functions for matrix and vector manipulations, including:

• Weighted Sum: multiple_in_single_out, computes the weighted sum of inputs.
• Matrix-Vector Multiplication: matrix_vector_multiplication, multiplies a matrix by a vector.
• Matrix-Matrix Multiplication: matrix_matrix_multiplication.
• Transpose Matrix: transpose_matrix.
• Vector Operations: Includes dot product, addition, subtraction, and scalar multiplication.

Getting Started

Prerequisites

• A C compiler (e.g., GCC)
• Make (optional, for building)

Installation

1. Clone the Repository: Start by cloning the repository to your local machine:

   git clone https://github.com/HanielUlises/Neural-Nets-C.git