Overview and simple trial of Convolutional Neural Network with MXnet

Actually I've known about MXnet for weeks as one of the most popular library / packages in Kaggler, but just recently I heard bug fix has been almost done and some friends say the latest version looks stable, so at last I installed it. I think that the most important feature of MXnet is its implementation of not only Deep Neural Network (DNN) but also Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) in R, because as far as I've known there has been no R packages implementing CNN (and/or RNN). In the original post of my blog, I tried a CNN {mxnet} R package with a short version of MNIST handwritten digit datasets whose maximum accuracy may be less than 0.98 for its small sample size. As a result, CNN of {mxnet} performed accuracy 0.976: this is better than Random Forest (0.951), Xgboost (0.953) or DNN by {h2o} (0.962). MXnet is a framework distributed by DMLC, the team also known as a distributor of Xgboost.