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Machine Learning for Cybersecurity Cookbook

You're reading from   Machine Learning for Cybersecurity Cookbook Over 80 recipes on how to implement machine learning algorithms for building security systems using Python

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Product type Paperback
Published in Nov 2019
Publisher Packt
ISBN-13 9781789614671
Length 346 pages
Edition 1st Edition
Languages
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Author (1):
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Emmanuel Tsukerman Emmanuel Tsukerman
Author Profile Icon Emmanuel Tsukerman
Emmanuel Tsukerman
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Table of Contents (11) Chapters Close

Preface 1. Machine Learning for Cybersecurity 2. Machine Learning-Based Malware Detection FREE CHAPTER 3. Advanced Malware Detection 4. Machine Learning for Social Engineering 5. Penetration Testing Using Machine Learning 6. Automatic Intrusion Detection 7. Securing and Attacking Data with Machine Learning 8. Secure and Private AI 9. Other Books You May Enjoy Appendix

Using Python virtual environments

Imagine that you have two projects—project A and project B—whose Python library requirements conflict. For instance, project A needs scikit-learn version 0.21, while project B requires scikit-learn versions >0.22. Or maybe one project requires Python 3.6 and the other Python 3.7. You could uninstall and then install the appropriate libraries or Python as you switch from one project to the other, but that can get tedious and impractical. To solve the problem of conflicting requirements, we recommend using Python virtual environments. You will see how to use a Python virtual environment in this recipe.

Getting ready

The module for virtual environments, venv, is included in the...

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