Tensorflow

import tensorflow as tf

mnist = tf.keras.datasets.mnist

(xTrain, yTrain), (xTest, yTest) = mnist.load_data()

xTrain, xTest = xTrain / 255, xTest / 255

network = 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="sigmoid")
])

predictions = network(xTrain[:1]).numpy()

loss = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True)

loss(yTrain[:1], predictions).numpy()

network.compile("adam", loss, ["accuracy"])

network.fit(xTrain, yTrain, epochs=5)

network.evaluate(xTest, yTest, verbose=2)

Tensorflow

python3 -m pip install --upgrade https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.12.0-py3-none-any.whl

Similar codes

0 vote208 views1 answer
Python round without math
Python
1 vote216 views1 answer
Open administrator command prompt using python
Python
27 votes216 views2 answers
What value do we get from NULL database python
Python
2 votes222 views1 answer
Kivy changing screen in python
Python
17 votes205 views2 answers
Make tkinter button disable
Python
3 votes203 views2 answers
Remove duplicates from sorted array
Python
7 votes217 views4 answers
Random word generator python
Python
1 vote215 views2 answers
Simple flask hello world
Python
1 vote209 views1 answer
Plot value counta
Python
0 vote237 views1 answer
Ion Flux Relabeling
Python