I am learning Neural Network. I was running following source code

import tensorflow as tf
from tensorflow import keras
import matplotlib.pyplot as plt
%matplotlib inline
import numpy as np
(X_train , y_train) , (X_test , y_test) = keras.datasets.mnist.load_data()

I was searching about keras mnist dataset. I found this. From that webpage I found 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. But, I was trying lot of datas. Finally, I thought to write plt.matshow(X_train[10010])

It outputs : enter image description here

As mnist digits classification were they had test set of 10,000 images. So, over than 10000 should return error. While it is showing more plots. Why?


You are actually plotting the train set with X_train which has 60k samples.

Try accessing X_test[10010] and it will indeed raise an IndexError.

keras.datasets.mnist.load_data() returns numpy.array objects, so you can check the shape of the arrays

>>> print("Train:", X_train.shape)
Train: (60000, 28, 28)
>>> print("Test:", X_test.shape)
Test: (10000, 28, 28)

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