Implementation of convolutional/fully connected neural network. The network layers include dropout layer, batch normalization layer, fully connected layer, rectified linear unit, convolutional layer, and max pooling layer. Various update rules including sgd with momentum, rmsprop, and adam are compared with the performance of vanila stochastic gradient descent.
My solution to Stanford Convolutional Neural Networks for Visual Recognition class project