Solving the Fashion MNIST with a simple neural network

Can computers recognize shirts from sandals?

Fashion MNIST dataset

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The first 20 photos and labels of the Fashion MNIST training set.
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See how each node is connected to every node in the adjacent layers?

Coding the neural network

%tensorflow_version 2.x
import tensorflow as tf
from tensorflow import keras
import numpy as np
import matplotlib.pyplot as plt
# load the fashion mnist dataset from keras
fashion_mnist = keras.datasets.fashion_mnist
(train_X, train_y),(test_X,test_y) = fashion_mnist.load_data()
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# data preprocessing, scaling values from 0-255 to 0-1
train_X = train_X/255.0
test_X = test_X/255.0
model = tf.keras.models.Sequential([ 
tf.keras.layers.Flatten(input_shape=(28, 28)),
tf.keras.layers.Dense(128, activation='relu'),
tf.keras.layers.Dense(10, activation='softmax')
])
model.compile(optimizer='adam',
loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),
metrics=['accuracy'])
model.fit(train_X, train_y, epochs=12)
loss, acc = model.evaluate(test_X, test_y, verbose = 1)
print('\\nTest accuracy: ', acc)
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