Problem Description
The MNIST database of handwritten digits (from 0 to 9) has a training set of 55,000
examples, and a test set of 10,000 examples. The digits have been size-normalized and
centered in a fixed-size image (28×28 pixels) with values from 0 to 1. You can use the
following code with TensorFlow in Python to download the data.
from keras.datasets import mnist
(x_train, y_train), (x_test, y_test) = mnist.load_data()
Every MNIST data point has two parts: an image of a handwritten digit and a
corresponding label. We will call the images ? and the labels ?. Both the training set and
test set contain ? and ?.
Each image is 28 pixels by 28 pixels and can be flattened into a vector of 28×28 = 784
numbers.
As mentioned, the corresponding labels in the MNIST are numbers between 0 and 9,
describing which digit a given image is of. In this assignment, we regard the labels as
one-hot vectors, i.e. 0 in most dimensions, a
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