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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

Machine Learning for Cybersecurity

In this chapter, we will cover the fundamental techniques of machine learning. We will use these throughout the book to solve interesting cybersecurity problems. We will cover both foundational algorithms, such as clustering and gradient boosting trees, and solutions to common data challenges, such as imbalanced data and false-positive constraints. A machine learning practitioner in cybersecurity is in a unique and exciting position to leverage enormous amounts of data and create solutions in a constantly evolving landscape.

This chapter covers the following recipes:

  • Train-test-splitting your data
  • Standardizing your data
  • Summarizing large data using principal component analysis (PCA)
  • Generating text using ...
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Publisher Resources

ISBN: 9781789614671Supplemental Content