mnist fashion dataset

import tensorflow as tf
from tensorflow.keras.datasets import fashion_mnist

link - https://github.com/zalandoresearch/fashion-mnist
#The data is already been sorted into traning and testing for us

(train_data, train_labels), (test_data, test_labels) = fashion_mnist.load_data()

#Create a small list so we can read the label as well
class_names = ['T-shirt/top', 'Trouser', 'Pullover', 'Dress', 'Coat', 'Sandle', 'Shirt', 'Sneaker', 'Bag', 'Ankle boot']

Here is what the above code is Doing:
1. The first line calls the load_data function from the fashion_mnist module. This function downloads the data,
splits it into training and testing sets, and returns those in the form of NumPy arrays.
2. The second line stores the class names in a list. These are the 10 different types of clothing that the model
can identify.