MNIST digits classification dataset
load_data function
tf_keras.datasets.mnist.load_data(path="mnist.npz")
Loads the MNIST dataset.
This is a dataset of 60,000 28x28 grayscale images of the 10 digits, along with a test set of 10,000 images. More info can be found at the MNIST homepage.
Arguments
- path: path where to cache the dataset locally
(relative to
~/.keras/datasets).
Returns
- Tuple of NumPy arrays:
(x_train, y_train), (x_test, y_test).
x_train: uint8 NumPy array of grayscale image data with shapes
(60000, 28, 28), containing the training data. Pixel values range
from 0 to 255.
y_train: uint8 NumPy array of digit labels (integers in range 0-9)
with shape (60000,) for the training data.
x_test: uint8 NumPy array of grayscale image data with shapes (10000, 28, 28), containing the test data. Pixel values range from 0 to 255.
y_test: uint8 NumPy array of digit labels (integers in range 0-9)
with shape (10000,) for the test data.
Example
(x_train, y_train), (x_test, y_test) = keras.datasets.mnist.load_data()
assert x_train.shape == (60000, 28, 28)
assert x_test.shape == (10000, 28, 28)
assert y_train.shape == (60000,)
assert y_test.shape == (10000,)
License: Yann LeCun and Corinna Cortes hold the copyright of MNIST dataset, which is a derivative work from original NIST datasets. MNIST dataset is made available under the terms of the Creative Commons Attribution-Share Alike 3.0 license.