epoch training loss epoch training loss epoch training loss epoch training loss epoch training loss epoch training loss test accuracy of the model on the , training test images finallywe evaluate the network performance using the test data set typical minibatch loss as function of iteration is shown in figure and the proposed neural network achieves about accuracy on the test set batch loss iteration figure the batch loss history further reading popular book written by some of the pioneers of deep learning is [ for an excellent and gentle introduction to the intuition behind neural networkswe recommend [ summary of many effective gradient descent methods for training of deep networks is given in [ an early resource on the limited-memory bfgs method is [ ]and more recent resource includes [ ]which makes recommendations on the best choice for the length of the bfgs history (that isthe value of the parameter hexercises show that the softmax function exp(zsoftmax exp(zk satisfies the invariance propertysoftmax(zsoftmax( )for any constant