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