Simple neural network playground I made to learn forward and backward propagation
The network consists of 2 hidden layers, each fallowed by an activation function, and outputs softmax probabilities for 2 classes. The training data type, training parameters and number of perceptron per layer can be changed.
The training progress of the network can be seen if the plot_output_during_training flag is set. Check out the jupyter notebook for more info.
Training data types: Linear, Circular, Check board
Sample NN output during training (tanh activation, circular training data):
