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

-4 votes128 views2 answers
The Dreamers
Python
0 vote138 views1 answer
Python file write all the bounding box coordinates using OpenCV
Python
0 vote132 views1 answer
Loading model
Python
3 votes159 views2 answers
How to restart program in python
Python
1 vote147 views1 answer
Adding variable in python
Python
1 vote121 views1 answer
Invoice parsing ocr python
Python
0 vote122 views1 answer
Return the intersection of this RDD and another one
Python
2 votes101 views3 answers
Creating a dictionary
Python
13 votes142 views4 answers
Python write list to text file
Python
0 vote138 views1 answer
Min of two numbers python
Python