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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

HIPAA data breaches – data exploration and visualization

Data exploration is the initial step in data analysis, whereby visual exploration is used to understand a dataset and the characteristics of the data. Data visualization helps us understand the data by placing it in an optical context so that our powerful visual processing centers can quickly find patterns and correlations in the data.

In this recipe, you will explore and visualize a public domain dataset regarding breaches of HIPAA confidential information.

Getting ready

For this recipe, you will need to install pandas and sklearn in pip. Use the following code to do so:

pip install pandas sklearn

In addition, the HIPAA-breach-report-2009-to-2017.csv...

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