MNIST database of handwritten digits

Dataset of 60,000 28x28 grayscale images of the 10 digits, along with a test set of 10,000 images.

Usage

dataset_mnist(path = "mnist.npz", convert = TRUE)

Arguments

path

Path where to cache the dataset locally (relative to ~/.keras/datasets).

convert

When TRUE (default) the datasets are returned as R arrays. If FALSE, objects are returned as NumPy arrays.

Value

Lists of training and test data: train$x, train$y, test$x, test$y, where x is an array of grayscale image data with shape (num_samples, 28, 28) and y is an array of digit labels (integers in range 0-9) with shape (num_samples).

str(dataset_mnist())

## List of 2
##  $ train:List of 2
##   ..$ x: int [1:60000, 1:28, 1:28] 0 0 0 0 0 0 0 0 0 0 ...
##   ..$ y: int [1:60000(1d)] 5 0 4 1 9 2 1 3 1 4 ...
##  $ test :List of 2
##   ..$ x: int [1:10000, 1:28, 1:28] 0 0 0 0 0 0 0 0 0 0 ...
##   ..$ y: int [1:10000(1d)] 7 2 1 0 4 1 4 9 5 9 ...

str(dataset_mnist(convert = FALSE))

## List of 2
##  $ train:List of 2
##   ..$ x: <numpy.ndarray shape(60000,28,28), dtype=uint8>
##   ..$ y: <numpy.ndarray shape(60000), dtype=uint8>
##  $ test :List of 2
##   ..$ x: <numpy.ndarray shape(10000,28,28), dtype=uint8>
##   ..$ y: <numpy.ndarray shape(10000), dtype=uint8>

See also

Other datasets:
dataset_boston_housing()
dataset_california_housing()
dataset_cifar10()
dataset_cifar100()
dataset_fashion_mnist()
dataset_imdb()
dataset_reuters()