(Code Supplied) High-performance C++/CUDA implementation of convolutional neural networks

***This is more about getting things running then optimizing a world-class algorithm*** I have the model and the following documentation: Compiling -- how to check out and compile this code. Data -- what kind of data this net can train on. LayerParams -- how to specify an architecture for the net. NeuronTypes -- types of hidden unit nonlinearities. TrainingNet -- how to train the net. Options -- the command-line arguments that the net takes. ViewingNet -- how to look inside the checkpoints saved by the net. CheckingGradients -- how to numerically test the gradients for correctness. The individual will need to use TeamViewer to access the machine. In addition, the machine has a NVIDIA geforce GTX 750 Ti GPU. Please take a look here: [login to view URL] This should be a simple process for individuals who know C++/CUDA. All the code is supplied.