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Mastering Machine Learning for Penetration Testing
book

Mastering Machine Learning for Penetration Testing

by Chiheb Chebbi
June 2018
Intermediate to advanced
276 pages
6h 26m
English
Packt Publishing
Content preview from Mastering Machine Learning for Penetration Testing

Questions

You are now able to build a machine learning model. Let's practice, putting our new skills to the test. In this chapter's GitHub repository, you will find a dataset that contains information about Android malware samples. Now you need to build your own model, following these instructions.

In the Chapter3-Practice GitHub repository, you will find a dataset that contains the feature vectors of more than 11,000 benign and malicious Android applications:

  1. Load the dataset using the pandas python library, and this time, add the low_memory=False parameter. Search for what that parameter does.
  2. Prepare the data that will be used for training.
  3. Split the data with the test_size=0.33 parameter.
  4. Create a set of classifiers that contains DecisionTreeClassifier() ...
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Publisher Resources

ISBN: 9781788997409