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Mastering Machine Learning for Penetration Testing

You're reading from   Mastering Machine Learning for Penetration Testing Develop an extensive skill set to break self-learning systems using Python

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Product type Paperback
Published in Jun 2018
Publisher Packt
ISBN-13 9781788997409
Length 276 pages
Edition 1st Edition
Languages
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Author (1):
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Chiheb Chebbi Chiheb Chebbi
Author Profile Icon Chiheb Chebbi
Chiheb Chebbi
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Toc

Table of Contents (13) Chapters Close

Preface 1. Introduction to Machine Learning in Pentesting FREE CHAPTER 2. Phishing Domain Detection 3. Malware Detection with API Calls and PE Headers 4. Malware Detection with Deep Learning 5. Botnet Detection with Machine Learning 6. Machine Learning in Anomaly Detection Systems 7. Detecting Advanced Persistent Threats 8. Evading Intrusion Detection Systems 9. Bypassing Machine Learning Malware Detectors 10. Best Practices for Machine Learning and Feature Engineering 11. Assessments 12. Other Books You May Enjoy

Best Practices for Machine Learning and Feature Engineering

In the previous chapters, we learned about the fundamentals of machine learning, and we learned how to build many different Python projects by using a suite of amazing open source Python libraries. Also, we dove into how to break machine learning models.

This last chapter will help you to build better models by illustrating many tips and best practices for different aspects of your projects.

In this chapter, we will cover the following:

  • An in-depth overview of feature engineering in machine learning
  • The best practices for machine learning
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