Handwritten-digit-recognition-using-neural-networks Implement the backpropagation algorithm for neural networks and apply it to the task of hand-written digit recognition. Files included in this exercise ex4.m - Octave/MATLAB script that steps you through the exercise ex4data1.mat - Training set of hand-written digits ex4weights.mat - Neural network parameters for exercise displayData.m - Function to help visualize the dataset fmincg.m - Function minimization routine (similar to fminunc) sigmoid.m - Sigmoid function computeNumericalGradient.m - Numerically compute gradients checkNNGradients.m - Function to help check your gradients debugInitializeWeights.m - Function for initializing weights predict.m - Neural network prediction function sigmoidGradient.m - Compute the gradient of the sigmoid function randInitializeWeights.m - Randomly initialize weights nnCostFunction.m - Neural network cost function