The DevOps movement brings application development and infrastructure operations together to increase efficiency and deploy applications more quickly Explore research at Microsoft a site featuring the impact of research along with publications products downloads and research careers Etymology According to the Oxford English Dictionary the first known use of the word quot computer quot was in 1613 in a book called The Yong Mans Gleanings by English Search for a book article website film or enter the information yourself The Lifecycle of a Revolution In the early days of the public internet we believed that we were helping build something totally new a world that would leave behind Microsoft Research Alumni Network If you were formerly an employee or intern at Microsoft Research join the newly formed LinkedIn Microsoft Research Alumni …Oracle acquired Sun Microsystems in 2010 and since that time Oracle s hardware and software engineers have worked side by side to build fully integrated systems and Artificial intelligence AI is intelligence exhibited by machines In computer science the field of AI research defines itself as the study of quot intelligent agents macOS is designed to take full advantage of the capabilities in every Mac It’s easy to use comes with amazing apps and helps protect your data Guides and Sample Code Search Guides and Sample Code Documents Copyright 169 2016 Apple Inc All rights reserved
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Book details
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Author : Mark Stamp
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Pages : 364 pages
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Publisher : Chapman and Hall/CRC 2017-08-11
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Language : English
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ISBN-10 : 1138626783
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ISBN-13 : 9781138626782
Book Synopsis
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.