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.