text: 
  
  #%% Modules
  
  import numpy as np
  import pathlib  # Object-oriented Filesystem Paths
  
  
  
  #$$ Function Definition -> get_mnist
  
  def get_mnist():
      
      with np.load( f"{pathlib.Path(__file__).parent.absolute()}/data/mnist.npz" ) as f:
          images, labels = f["x_train"], f["y_train"]
          
      images = images.astype("float32") / 255  # Cast a copy of the images array to 32-bit floating point representation.
      images = np.reshape(images, (images.shape[0], images.shape[1] * images.shape[2]))
      
      labels = np.eye(10)[labels]
      
      return images, labels
  
  
  
  #%% Validate returned variables -> images, labels
      
  images, labels = get_mnist()
      
  # print( type(images) )
  # print( images.shape )  # 60000-by-784 -> Each row contains a 1-Tuple of 784 values (i.e. 28-by-28).
  
  # print( type(labels) )
  # print( labels.shape )  # 60000-by-1 -> Each row contains an array of zeros/ones that indicate the labeled digit (i.e. 0-9).
  
  
  