TensorFlow Machine Learning Projects

Logistic regression with Keras

Keras is a high-level library that is available as part of TensorFlow. In this section, we will rebuild the same model we built earlier with TensorFlow core with Keras:

1. Keras takes data in a different format, and so we must first reformat the data using datasetslib:

x_train_im = mnist.load_images(x_train)x_train_im, x_test_im = x_train_im / 255.0, x_test / 255.0

In the preceding code, we are loading the training images in memory before both the training and test images are scaled, which we do by dividing them by 255.

2. Then, we build the model:

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

3. Compile the model with the sgd optimizer. Set ...