Implement backpropagation training algorithm

I've completed the implementation of BP algorithm, with Eigen 3 (without MKL at the current stage). I tested MNIST dataset on my PC, some basic performance stats are listed as below:

NN layers: 4
NN type: fully-connected
NN structure: 784 (input layer) -> 1024 (hidden layer) -> 1024 (hidden layer) -> 10 (output layer)
Dataset for training/testing: MNIST (60,000 samples for training, 10,000 samples for testing)
NN training time (one epoch): 14 seconds (Single thread with CPU Intel Core i7-3770 @ 3.4GHz)
NN testing accuracy (after one epoch training): 96%

Sorry that I'm not familiar with the standard workflow of adding a new module in Shogun, and also encounter problems of how to deal with the dataset (400+MB). Hope some ardent guy can help me, thanks!