We will use the package MXNet R to build our neural networks. It implements state-of-the-art deep learning algorithms and enables efficient GPU computing. We can work in our familiar R environment and at the same time harness the power of the GPUs (though access to GPU is available through the Python API now, we still need to wait for it to be available for R). It will be useful to give you a small overview about the basic building blocks of MXNet before we start using it for our time series predictions.
Note
Refer to the https://github.com/apache/incubator-mxnet/tree/master/R package for more details on the MXNet R package.
In MXNet, NDArray is the basic operation unit. It's a vectorized operation unit for matrix and tensor computations. All operations on this operation unit can be run on either the CPU or GPUs. The most important point is that all these operations are parallel. It's the basic data structure for manipulating and playing around with data...