DeepLearningIntro/DeepLearningIntro/Tutorial.py at master · Fletch153/DeepLearningIntro · GitHub

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import tensorflow as tf

import matplotlib.pyplot as plt

import numpy as np

mnist = tf.keras.datasets.mnist # 28x28 images of hand-written digits 0-9

(x_train, y_train), (x_test, y_test) = mnist.load_data()

x_train = tf.keras.utils.normalize(x_train, axis=1)

x_test = tf.keras.utils.normalize(x_test, axis=1)

model = tf.keras.models.Sequential()

model.add(tf.keras.layers.Flatten())

model.add(tf.keras.layers.Dense(128, activation=tf.nn.relu))

model.add(tf.keras.layers.Dense(10, activation=tf.nn.softmax))

model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])

model.fit(x_train, y_train, epochs=1)

predictions = model.predict([x_test])

print("Prediction for first letter:", np.argmax(predictions[0]))

plt.imshow(x_test[0])

plt.show()

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