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Machine Learning for Cybersecurity Cookbook
book

Machine Learning for Cybersecurity Cookbook

by Emmanuel Tsukerman
November 2019
Intermediate to advanced content levelIntermediate to advanced
346 pages
9h 36m
English
Packt Publishing
Content preview from Machine Learning for Cybersecurity Cookbook

How to do it...

  1. Begin by defining a few convenience functions for pre-processing the MNIST dataset:
import tensorflow as tfdef preprocess_observations(data):    """Preprocesses MNIST images."""    data = np.array(data, dtype=np.float32) / 255    data = data.reshape(data.shape[0], 28, 28, 1)    return datadef preprocess_labels(labels):    """Preprocess MNIST labels."""    labels = np.array(labels, dtype=np.int32)    labels = tf.keras.utils.to_categorical(labels, num_classes=10)
  1. Write a convenience function to load MNIST:
def load_mnist():    """Loads the MNIST dataset."""    (X_train, y_train), (X_test, y_test) = tf.keras.datasets.mnist.load_data()    X_train = preprocess_observations(X_train)    X_test = preprocess_observations(X_test) y_train = preprocess_labels(y_train) ...
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Publisher Resources

ISBN: 9781789614671Supplemental Content