6. Neural Networks and Deep Learning

Activity 6.01: Finding the Best Accuracy Score for the Digits Dataset

Solution:

1. Open a new Jupyter Notebook file.
2. Import tensorflow.keras.datasets.mnist as mnist:

   import tensorflow.keras.datasets.mnist as mnist

3. Load the mnist dataset using mnist.load_data() and save the results into (features_train, label_train), (features_test, label_test):

   (features_train, label_train), \
   (features_test, label_test) = mnist.load_data()

4. Print the content of label_train:

   label_train

   The expected output is this:

   array([5, 0, 4, ..., 5, 6, 8], dtype=uint8)

   The label column contains numeric values that correspond to the 10 handwritten digits: 0 to 9.

5. Print the shape of the training set:

   features_train.shape

   The expected output is this:

   (60000, 28, 28)

   The training set is composed of 60,000 observations of shape 28 by 28. We will need to flatten the input for our neural network.

6. Print the shape of the testing set:

   features_test.shape

   The expected...