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.

• PrefaceAbout 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 EpilogueReferences Index

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.

• PrefaceAbout 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 EpilogueReferences Index

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.

• PrefaceAbout 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 EpilogueReferences Index