A Simple MNIST Digit Classifier Neural Network that recognises hand-written numerical digits from the MNIST Digit Recogniser Dataset made from scratch* in Python with 7960 trainable parameters using Forward Propagation, Back propagation, ReLu & Softmax Activation Functions. It uses a 2-layer neural network that has an input layer consisting of 784 neurons (28x28 pixels), one hidden layers consisting of 10 neurons with ReLu (Rectified Linear unit) activation function and an output layer consisting of 10 neurons with Softmax activation function.
