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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…

In the next steps, we will convert a corpus of text data into numerical form, amenable to machine learning algorithms:

  1. First, import a textual dataset:
with open("anonops_short.txt", encoding="utf8") as f:    anonops_chat_logs = f.readlines()
  1. Next, count the words in the text using the hash vectorizer and then perform weighting using tf-idf:
from sklearn.feature_extraction.text import HashingVectorizerfrom sklearn.feature_extraction.text import TfidfTransformermy_vector = HashingVectorizer(input="content", ngram_range=(1, 2))X_train_counts = my_vector.fit_transform(anonops_chat_logs,)tf_transformer = TfidfTransformer(use_idf=True,).fit(X_train_counts)X_train_tf = tf_transformer.transform(X_train_counts)
  1. The end result is a ...
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Publisher Resources

ISBN: 9781789614671Supplemental Content