This book states that the major aim audience are people who have some familiarity with Internet of things (IoT) but interested to get a comprehensive interpretation of the role of deep Learning in maintaining the security and privacy of IoT. A reader should be friendly with Python and the basics of machine learning and deep learning. Interpretation of statistics and probability theory will be a plus but is not certainly vital for identifying most of the book's material.
"synopsis" may belong to another edition of this title.
This book states that the major aim audience are people who have some familiarity with Internet of things (IoT) but interested to get a comprehensive interpretation of the role of deep Learning in maintaining the security and privacy of IoT. A reader should be friendly with Python and the basics of machine learning and deep learning. Interpretation of statistics and probability theory will be a plus but is not certainly vital for identifying most of the book's material.
"About this title" may belong to another edition of this title.
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Taschenbuch. Condition: Neu. Deep Learning Techniques for IoT Security and Privacy | Mohamed Abdel-Basset (u. a.) | Taschenbuch | xxi | Englisch | 2022 | Springer | EAN 9783030890278 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Seller Inventory # 125801345
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book states that the major aim audience are people who have some familiarity with Internet of things (IoT) but interested to get a comprehensive interpretation of the role of deep Learning in maintaining the security and privacy of IoT. A reader should be friendly with Python and the basics of machine learning and deep learning. Interpretation of statistics and probability theory will be a plus but is not certainly vital for identifying most of the book's material.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 280 pp. Englisch. Seller Inventory # 9783030890278
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