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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032207175 ISBN 13: 9781032207179
Language: English
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Published by Chapman and Hall/CRC, 2017
ISBN 10: 1138626783 ISBN 13: 9781138626782
Language: English
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Published by Chapman and Hall/CRC, 2022
ISBN 10: 1032204923 ISBN 13: 9781032204925
Language: English
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Published by Chapman and Hall/CRC, 2022
ISBN 10: 1032204923 ISBN 13: 9781032204925
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Published by Chapman and Hall/CRC, 2022
ISBN 10: 1032204923 ISBN 13: 9781032204925
Language: English
Seller: Basi6 International, Irving, TX, U.S.A.
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032207175 ISBN 13: 9781032207179
Language: English
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032207175 ISBN 13: 9781032207179
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032207175 ISBN 13: 9781032207179
Language: English
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Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032207175 ISBN 13: 9781032207179
Language: English
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Paperback. Condition: new. Paperback. 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. The book is accessible and doesnt prove theorems, or 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 classic machine learning topics in depth, including Hidden Markov Models (HMM), Support Vector Machines (SVM), and clustering. Additional machine learning topics include k-Nearest Neighbor (k-NN), boosting, Random Forests, and Linear Discriminant Analysis (LDA). The fundamental deep learning topics of backpropagation, Convolutional Neural Networks (CNN), Multilayer Perceptrons (MLP), and Recurrent Neural Networks (RNN) are covered in depth. A broad range of advanced deep learning architectures are also presented, including Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), Extreme Learning Machines (ELM), Residual Networks (ResNet), Deep Belief Networks (DBN), Bidirectional Encoder Representations from Transformers (BERT), and Word2Vec. Finally, several cutting-edge deep learning topics are discussed, including dropout regularization, attention, explainability, and adversarial attacks.Most of the examples in the book are drawn from the field of information security, with many of the machine learning and deep learning applications focused on malware. The applications presented serve to demystify the topics by illustrating the use of various learning techniques in straightforward scenarios. Some of the exercises in this book require programming, and elementary computing concepts are assumed in a few of the application sections. However, anyone with a modest amount of computing 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: /~stamp/ML/. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032207175 ISBN 13: 9781032207179
Language: English
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032207175 ISBN 13: 9781032207179
Language: English
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Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032207175 ISBN 13: 9781032207179
Language: English
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Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032207175 ISBN 13: 9781032207179
Language: English
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. pages cm Second edition Includes bibliographical references and index.
Published by Chapman and Hall/CRC, 2024
ISBN 10: 1032207175 ISBN 13: 9781032207179
Language: English
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Published by Chapman and Hall/CRC, 2022
ISBN 10: 1032204923 ISBN 13: 9781032204925
Language: English
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Published by Chapman and Hall/CRC, 2022
ISBN 10: 1032204923 ISBN 13: 9781032204925
Language: English
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Published by Chapman and Hall/CRC, 2022
ISBN 10: 1032204923 ISBN 13: 9781032204925
Language: English
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Published by Chapman and Hall/CRC, 2022
ISBN 10: 1032204923 ISBN 13: 9781032204925
Language: English
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition.
Published by Chapman and Hall/CRC, 2017
ISBN 10: 1138626783 ISBN 13: 9781138626782
Language: English
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: New.
Published by Taylor & Francis Ltd, London, 2017
ISBN 10: 1138626783 ISBN 13: 9781138626782
Language: English
Seller: Grand Eagle Retail, Fairfield, OH, U.S.A.
Hardcover. Condition: new. Hardcover. 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 doesnt 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: /~stamp/ML/. For the readers benefit, the figures in the book are also available in electronic form, and in color.About the AuthorMark 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 masters student projects, most of which involve a combination of information security and machine learning. This class-tested textbook will provide in-depth coverage of the fundamentals of machine learning, with an exploration of applications in information security. The book will cover malware detection, cryptography, and intrusion detection. The book will be relevant for students in machine learning and computer security courses. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Published by Chapman and Hall/CRC, 2017
ISBN 10: 1138626783 ISBN 13: 9781138626782
Language: English
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition.
Published by Chapman and Hall/CRC 2017-09-26, 2017
ISBN 10: 1138626783 ISBN 13: 9781138626782
Language: English
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Published by Chapman and Hall/CRC, 2022
ISBN 10: 1032204923 ISBN 13: 9781032204925
Language: English
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Published by T And F Crc Press, 2023
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Published by Chapman and Hall/CRC, 2017
ISBN 10: 1138626783 ISBN 13: 9781138626782
Language: English
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Published by Taylor & Francis Ltd, 2022
ISBN 10: 1032204923 ISBN 13: 9781032204925
Language: English
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Published by Taylor & Francis Ltd, 2017
ISBN 10: 1138626783 ISBN 13: 9781138626782
Language: English
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First Edition
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Published by Chapman and Hall/CRC, 2022
ISBN 10: 1032204923 ISBN 13: 9781032204925
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Published by Taylor & Francis Ltd, 2017
ISBN 10: 1138626783 ISBN 13: 9781138626782
Language: English
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