Introduction to Machine Learning with Applications in Information Security (Hardback)
  • Introduction to Machine Learning with Applications in Information Security (Hardback)
zoom

Introduction to Machine Learning with Applications in Information Security (Hardback)

(author)
£49.99
Hardback 346 Pages / Published: 26/09/2017
  • We can order this

Usually dispatched within 2 weeks

  • This item has been added to your basket

Introduction to Machine Learning with Applications in Information Security provides a class-tested introduction to a wide variety of machine learning algorithms, reinforced through realistic applications. The book is accessible and doesn't prove theorems, or otherwise dwell on mathematical theory. The goal is to present topics at an intuitive level, with just enough detail to clarify the underlying concepts.

The book covers core machine learning topics in-depth, including Hidden Markov Models, Principal Component Analysis, Support Vector Machines, and Clustering. It also includes coverage of Nearest Neighbors, Neural Networks, Boosting and AdaBoost, Random Forests, Linear Discriminant Analysis, Vector Quantization, Naive Bayes, Regression Analysis, Conditional Random Fields, and Data Analysis.

Most of the examples in the book are drawn from the field of information security, with many of the machine learning applications specifically focused on malware. The applications presented are designed to demystify machine learning techniques by providing straightforward scenarios. Many of the exercises in this book require some programming, and basic computing concepts are assumed in a few of the application sections. However, anyone with a modest amount of programming experience should have no trouble with this aspect of the book.

Instructor resources, including PowerPoint slides, lecture videos, and other relevant material are provided on an accompanying website: http://www.cs.sjsu.edu/~stamp/ML/. For the reader's benefit, the figures in the book are also available in electronic form, and in color.

About the Author

Mark Stamp has been a Professor of Computer Science at San Jose State University since 2002. Prior to that, he worked at the National Security Agency (NSA) for seven years, and a Silicon Valley startup company for two years. He received his Ph.D. from Texas Tech University in 1992. His love affair with machine learning began in the early 1990s, when he was working at the NSA, and continues today at SJSU, where he has supervised vast numbers of master's student projects, most of which involve a combination of information security and machine learning.

Publisher: Taylor & Francis Ltd
ISBN: 9781138626782
Number of pages: 346
Weight: 658 g
Dimensions: 235 x 156 mm

You may also be interested in...

The Truth Machine
Added to basket
Hello World
Added to basket
£18.99
Hardback
Intercept
Added to basket
£8.99
Paperback
The Old Religion
Added to basket
£12.99
Hardback
Blockchain Basics
Added to basket
Cyberphobia
Added to basket
£9.99
Paperback
Surveillance Valley
Added to basket
£14.99
Paperback
Ghost in the Wires
Added to basket
Helping Kids with Coding For Dummies
Added to basket
Democracy Hacked
Added to basket
£16.99
Hardback
Hacking For Dummies
Added to basket
£23.99
Paperback
Cyber Wars
Added to basket
£14.99
Paperback
The Cyber Effect
Added to basket
£10.99
Paperback
Data and Goliath
Added to basket
£12.99
Paperback
DarkMarket
Added to basket
£10.99
Paperback

Reviews

Please sign in to write a review

Your review has been submitted successfully.