Deep Learning with R Cookbook

How to do it...

The MNIST dataset is included in keras and can be accessed using the dataset_mnist() function:

1. Let's load the data into the R environment:

mnist <- dataset_mnist()x_train <- mnist$train$xy_train <- mnist$train$yx_test <- mnist$test$xy_test <- mnist$test$y

2. Our training data is of the form (images, width, height). Due to this, we'll convert the data into a one-dimensional array and rescale it:

# Reshaping the datax_train <- array_reshape(x_train , c(nrow(x_train),784))x_test <- array_reshape(x_test , c(nrow(x_test),784))# Rescaling the datax_train <- x_train/255x_test <- x_test/255

3. Our target data is an integer vector and contains values from 0 to 9. We need to one-hot encode our target variable in order to convert it into ...