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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...

The code for the following can be found on https://github.com/PacktPublishing/Machine-Learning-for-Cybersecurity-Cookbook/blob/master/Chapter02/Classifying%20Files%20by%20Type/File%20Type%20Classifier.ipynb. We build a classifier using this data to predict files as JavaScript, Python, or PowerShell:

  1. Begin by importing the necessary libraries and specifying the paths of the samples we will be using to train and test:
import osfrom sklearn.feature_extraction.text import HashingVectorizer, TfidfTransformerfrom sklearn.ensemble import RandomForestClassifierfrom sklearn.model_selection import train_test_splitfrom sklearn.metrics import accuracy_score, confusion_matrixfrom sklearn.pipeline import Pipeline  javascript_path = "/path/to/JavascriptSamples/" ...
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Publisher Resources

ISBN: 9781789614671Supplemental Content