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README.md
activations.png
cumulative_plot.m
encode_labels.m
evaluate.m
minimize.m
mnist_all.mat
neural_network.m
neural_network_cost.m
normalize.m
predict.m
roll.m
shuffle_data.m
sigmoid.m
sigmoidGradient.m
softmax.m
test.m
theta.mat
unroll.m adding Simple language + assembly, as well as MATLAB neural networks Dec 9, 2012

README.md

This is an implementation of a feed-forward backpropogating neural network in Matlab. It achieves over 95% recognition accuracy on MNIST digit recognition data.

To train it, use the following code:

s = rng; % Store random number generator state
params = test; % Train network on random subset (and do cross-validation)
params.iterations = 300; % Set iterations
rng(s);
theta = test(params); % Train final network
rng(s);
test(theta); % Test final network