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Verlag: Chapman and Hall/CRC (edition 1), 2022
ISBN 10: 1032401001 ISBN 13: 9781032401003
Sprache: Englisch
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Verlag: Taylor & Francis Ltd, London, 2022
ISBN 10: 1032401001 ISBN 13: 9781032401003
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: new. Paperback. Cybersecurity Analytics is for the cybersecurity student and professional who wants to learn data science techniques critical for tackling cybersecurity challenges, and for the data science student and professional who wants to learn about cybersecurity adaptations. Trying to build a malware detector, a phishing email detector, or just interested in finding patterns in your datasets? This book can let you do it on your own. Numerous examples and datasets links are included so that the reader can "learn by doing." Anyone with a basic college-level calculus course and some probability knowledge can easily understand most of the material. The book includes chapters containing: unsupervised learning, semi-supervised learning, supervised learning, text mining, natural language processing, and more. It also includes background on security, statistics, and linear algebra. The website for the book contains a listing of datasets, updates, and other resources for serious practitioners. This book organizes in one place the mathematics, probability, statistics and machine learning information that is required for a practitioner of cybersecurity analytics, as well as the basics of cybersecurity needed for a practitioner. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Verlag: Chapman and Hall/CRC 2022-08-29, 2022
ISBN 10: 1032401001 ISBN 13: 9781032401003
Sprache: Englisch
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In den WarenkorbZustand: New. 1st edition NO-PA16APR2015-KAP.
Verlag: Taylor and Francis Ltd, GB, 2022
ISBN 10: 1032401001 ISBN 13: 9781032401003
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: New. Cybersecurity Analytics is for the cybersecurity student and professional who wants to learn data science techniques critical for tackling cybersecurity challenges, and for the data science student and professional who wants to learn about cybersecurity adaptations. Trying to build a malware detector, a phishing email detector, or just interested in finding patterns in your datasets? This book can let you do it on your own. Numerous examples and datasets links are included so that the reader can "learn by doing." Anyone with a basic college-level calculus course and some probability knowledge can easily understand most of the material. The book includes chapters containing: unsupervised learning, semi-supervised learning, supervised learning, text mining, natural language processing, and more. It also includes background on security, statistics, and linear algebra. The website for the book contains a listing of datasets, updates, and other resources for serious practitioners.
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In den WarenkorbZustand: As New. Unread book in perfect condition.
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In den WarenkorbZustand: New. 2022. 1st Edition. Paperback. . . . . .
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In den WarenkorbPaperback. Zustand: Brand New. 356 pages. 10.00x7.00x0.79 inches. In Stock.
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In den WarenkorbZustand: New. Rakesh Verma is a professor of computer science at the University of Houston where he is leading a research group that applies reasoning and data science to cybersecurity challenges. He teaches a course on security analytics that include.
Verlag: Chapman and Hall/CRC 2019-11-15, 2019
ISBN 10: 036734601X ISBN 13: 9780367346010
Sprache: Englisch
Anbieter: Chiron Media, Wallingford, Vereinigtes Königreich
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In den WarenkorbTaschenbuch. Zustand: Neu. Neuware - This book organizes in one place the mathematics, probability, statistics and machine learning information that is required for a practitioner of cybersecurity analytics, as well as the basics of cybersecurity needed for a practitioner.
Verlag: Taylor & Francis Ltd, London, 2022
ISBN 10: 1032401001 ISBN 13: 9781032401003
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: new. Paperback. Cybersecurity Analytics is for the cybersecurity student and professional who wants to learn data science techniques critical for tackling cybersecurity challenges, and for the data science student and professional who wants to learn about cybersecurity adaptations. Trying to build a malware detector, a phishing email detector, or just interested in finding patterns in your datasets? This book can let you do it on your own. Numerous examples and datasets links are included so that the reader can "learn by doing." Anyone with a basic college-level calculus course and some probability knowledge can easily understand most of the material. The book includes chapters containing: unsupervised learning, semi-supervised learning, supervised learning, text mining, natural language processing, and more. It also includes background on security, statistics, and linear algebra. The website for the book contains a listing of datasets, updates, and other resources for serious practitioners. This book organizes in one place the mathematics, probability, statistics and machine learning information that is required for a practitioner of cybersecurity analytics, as well as the basics of cybersecurity needed for a practitioner. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Verlag: Taylor and Francis Ltd, GB, 2022
ISBN 10: 1032401001 ISBN 13: 9781032401003
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: New. Cybersecurity Analytics is for the cybersecurity student and professional who wants to learn data science techniques critical for tackling cybersecurity challenges, and for the data science student and professional who wants to learn about cybersecurity adaptations. Trying to build a malware detector, a phishing email detector, or just interested in finding patterns in your datasets? This book can let you do it on your own. Numerous examples and datasets links are included so that the reader can "learn by doing." Anyone with a basic college-level calculus course and some probability knowledge can easily understand most of the material. The book includes chapters containing: unsupervised learning, semi-supervised learning, supervised learning, text mining, natural language processing, and more. It also includes background on security, statistics, and linear algebra. The website for the book contains a listing of datasets, updates, and other resources for serious practitioners.
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In den WarenkorbZustand: New.
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