Configurable Feed-Forward Backpropagation Neural Network written in C++ from Scratch.
- Number of Layers
- Number of neurons in each Layer
- Activation Function for each Layer (ReLU, Sigmoid, TanH, Softmax)
- Network Architecture (Fully Connected / Partially Connected)
- L2 Regularization Strength to Avoid Overfitting
- Clone the repository
- Compile and run neural_network.cpp
- Enter asked inputs
- Training starts inputted iterations
- Check predicted outputs and accuracy in prediction.txt