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Introduction to Machine Learning with Applications in Information Security, Second Edition provides a classroom-tested introduction to a wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications.
Mark Stamp is a Professor at San Jose State University, and the author of two textbooks, Information Security: Principles and Practice and Applied Cryptanalysis: Breaking Ciphers in the Real World. He previously worked at the National Security Agency (NSA) for seven years, which was followed by two years at a small Silicon Valley startup company.
- Preface About the Author - What is Machine Learning? - A Revealing Introduction to Hidden Markov Models - Principles of Principal Component Analysis - A Reassuring Introduction to Support Vector Machines - A Comprehensible Collection of Clustering Concepts - Many Mini Topics - Deep Thoughts on Deep Learning - Onward to Backpropagation - A Deeper Diver into Deep Learning - Alphabet Soup of Deep Learning Topics - HMMs for Classic Cryptanalysis - Image Spam Detection - Image-Based Malware Analysis - Malware Evolution Detection - Experimental Design and Analysis - Epilogue References Index
