library(readr)
library(nnet)

train <- read_csv("../input/train.csv")
test <- read_csv("../input/test.csv")

inTrain<-sample(1:nrow(train),50)

label<-train[inTrain,1]
train<-train[inTrain,-1]
train<-train/256
test<-test/256

nn<-multinom(label~.,
             data=train,
             MaxNWts=10000,
             maxit=100)

predictions<-data.frame(Imageid=1:nrow(test),Label=NA)

predictions[,2]<-predict(nn,test,type='class')

predictions[1:100,]
write.csv(predictions,'nnet.csv',row.names=F)