003fashion_mnist.py

#!/usr/bin/env python
# coding: utf-8

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import tensorflow as tf 
print (tf.__version__)


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mnist=tf.keras.datasets.fashion_mnist
(training_images,training_labels),(test_images,test_labels)=mnist.load_data()
import matplotlib.pyplot as plt
plt.imshow(training_images[10086])
print(training_labels[10086])
print(training_images[10086])
training_images=training_images/ 255.0
test_images=test_images/255.0


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model = tf.keras.models.Sequential([tf.keras.layers.Flatten(),
                                   tf.keras.layers.Dense(128,activation=tf.nn.relu),
                                   tf.keras.layers.Dense(10,activation=tf.nn.softmax)])


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model.compile(optimizer = tf.optimizers.Adam(),
              loss='sparse_categorical_crossentropy')
model.fit(training_images,training_labels,epochs=5)


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model.evaluate(test_images,test_labels)


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