Download Mastering Machine Learning for Penetration Testing: Develop an extensive skill set to break self-learning systems using Python, by Chiheb Chebbi
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Mastering Machine Learning for Penetration Testing: Develop an extensive skill set to break self-learning systems using Python, by Chiheb Chebbi
Download Mastering Machine Learning for Penetration Testing: Develop an extensive skill set to break self-learning systems using Python, by Chiheb Chebbi
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Product details
Paperback: 276 pages
Publisher: Packt Publishing (June 27, 2018)
Language: English
ISBN-10: 1788997409
ISBN-13: 978-1788997409
Product Dimensions:
7.5 x 0.6 x 9.2 inches
Shipping Weight: 1.3 pounds (View shipping rates and policies)
Average Customer Review:
3.0 out of 5 stars
2 customer reviews
Amazon Best Sellers Rank:
#1,457,692 in Books (See Top 100 in Books)
While this book does an excellent job of describing many aspects of Machine Learning, it doesn't live up to its title of showing you how to apply M.L. techniques to Penetration Testing.**HOWEVER** If this book was retitled: "M.L. for Dummies", I would give it 5 stars!!! Note that I'm not mocking the author or potential reader - it really is an **excellent** introduction for newcomers to the M.L. field - exactly what the "...for Dummies" book series is intended to be!The vast majority of this book is spent describing concepts and algorithms for M.L., which I feel the author is very technically qualified to teach. His writing style is very approachable, and he is very, very adept at relating these complicated topics to newcomers in the M.L. field. In fact, I don't recall another source that can convey, in so few words, these deeply technical thoughts as easily as this book.The closest thing in this book describing M.L. "for Pentesting" is probably the 40 pages of chapters 8 and 9, which mostly name-drop various tools that can be used to investigate perturbing training data to influence an M.L. model's classification capabilities. No mention is made in this section on how to use these tools and techniques for *Penetration* *Testing* - only for perturbing training data, which the author doesn't describe how to utilize for an actual Pentest-type of attack!Chapter 10 may be the most undersold chapter in this book. It covers best practices for Feature Engineering - something that you *must* master in order to use M.L. The lucid descriptions in this chapter, alone, almost justified my purchase price!Again, I think this is a great book written by a very competent author who has a gift for conveying very detailed technical matter in an easy-to-grasp way. His writing style is very approachable, and this book is an easy read for the newcomer to M.L.In fact, if you are new to M.L., I recommend reading this book, first, to see if it is even something that you may want to partake of.But - again - this book is *not* a "Machine Learning for Pentesting" book. It doesn't come close to hitting this mark, in my opinion.
For me, this was a good introduction to Machine Learning with regards to Pentesting. Some interesting concepts and just enough information to wet your appetite to look further into ML. Recommend it for anyone with an interest to get a good base to start at.
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