A basic implementation of a Multi-Layer Perceptron in C++.
The purpose of this project is to understand the working principle of neural networks by building a network from scratch and feeding it with custom data.
Please check source files for more details:
- You can find the implementation of various parts of the neural network, going from a simple
neuron
, to alayer
, to the wholenetwork
. - Both weight and bias neurons are implemented.
- The topology (depth of the network, along with the number of neurons in each layer) could be specified in the
Data.txt
file. - The data generator actually simulates the behavior of a XOR gate and outputs training data in a non-generic format (Not CSV).
Ressources: