mnist_digits_basic1.py

# -*- coding: utf-8 -*-
"""
Created on Mon Apr  6 22:10:10 2020

@author: samuel
"""


import tensorflow as tf

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

model.compile(optimizer='adam',loss='sparse_categorical_crossentropy',metrics=['accuracy'])
model.fit(x_train,y_train,epochs=3)
import matplotlib.pyplot as plt


val_loss, val_acc =model.evaluate(x_test,y_test)


plt.imshow(x_train[0],cmap=plt.cm.binary)
plt.show()