By request from students, I have compiled a little list of the books that are currently out teaching ML+CS, as well as a minimal summary of each. They’re not ranked in any order. Check them out and feel free to comment below.

Malware Data Science: Attack Detection and Attribution

Book by Hillary Sanders and Joshua Saxe

Personal one-sentence summary: teaches both basic and advanced tools for malware detection.

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Mastering Machine Learning for Penetration Testing: Develop an extensive skill set to break self-learning systems using Python

Book by Chiheb Chebbi

Personal one-sentence summary: a good introduction to core data science concepts.

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Machine Learning and Security: Protecting Systems with Data and Algorithms
Book by Clarence Chio and David Freeman

Personal one-sentence summary: good academic guide that helps a practitioner be aware of possible pitfalls in the field.

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Hands-On Machine Learning for Cybersecurity: Safeguard your system by making your machines intelligent using the Python ecosystem
Book by Soma Halder and Sinan Ozdemir

Personal one-sentence summary: great theoretical overview as well as a selection of nice case studies.

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Machine Learning for Cybersecurity Cookbook
Book by Emmanuel Tsukerman

Personal one-sentence summary: 80+ solutions to common cybersecurity data science problems.

Expected to come out in July. Subscribe to my newsletter to be the first to know about it!

*As an Amazon Associate I earn from qualifying purchases.