R Package Name	Brief Description
nnet	This package provides support for feed-forward networks with a single hidden layer. It can minimize either the sum of squares error or cross-entropy as its objective function (when finding a good set of weights for each neuron during training).
neuralnet	This package provides support for feedforward networks with any number of hidden layers. It contains multiple variants of the backpropagation algorithm for training, allows the user to choose different activation functions for the hidden neurons (e.g., logistic and hyperbolic tangent), and also can minimize either sum of squares error or cross-entropy as its objective function. Functions are also provided for visualizing the network after training.
mxnet	This advanced package provides access to the popular MXNet Scalable Deep Learning framework in R, which can be used to create standard or deep feed-forward networks, as well as advanced models such as recurrent (for sequential data) and convolutional (for spatially related data such as images) neural networks. Support is also provided for training networks with video cards (also known as graphics processing units, GPUs) in order to speed up training.