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    Machine Learning Security Principles. Keep data, networks, users, and applications safe from prying eyes

    (ebook) (audiobook) (audiobook) Język publikacji: angielski
    Machine Learning Security Principles. Keep data, networks, users, and applications safe from prying eyes John Paul Mueller, Rod Stephens - okładka ebooka

    Machine Learning Security Principles. Keep data, networks, users, and applications safe from prying eyes John Paul Mueller, Rod Stephens - okładka ebooka

    Machine Learning Security Principles. Keep data, networks, users, and applications safe from prying eyes John Paul Mueller, Rod Stephens - okładka audiobooka MP3

    Machine Learning Security Principles. Keep data, networks, users, and applications safe from prying eyes John Paul Mueller, Rod Stephens - okładka audiobooks CD

    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    450
    Czas nagrania:
    8 godz. 53 min.
    Dostępne formaty:
    PDF
    ePub
     
    Audiobook w mp3

    Ebook

    139,00 zł

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    Audiobook w mp3

    159,00 zł

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    Do przechowalni

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    Businesses are leveraging the power of AI to make undertakings that used to be complicated and pricy much easier, faster, and cheaper. The first part of this book will explore these processes in more depth, which will help you in understanding the role security plays in machine learning.
    As you progress to the second part, you’ll learn more about the environments where ML is commonly used and dive into the security threats that plague them using code, graphics, and real-world references.
    The next part of the book will guide you through the process of detecting hacker behaviors in the modern computing environment, where fraud takes many forms in ML, from gaining sales through fake reviews to destroying an adversary’s reputation. Once you’ve understood hacker goals and detection techniques, you’ll learn about the ramifications of deep fakes, followed by mitigation strategies.
    This book also takes you through best practices for embracing ethical data sourcing, which reduces the security risk associated with data. You’ll see how the simple act of removing personally identifiable information (PII) from a dataset lowers the risk of social engineering attacks.
    By the end of this machine learning book, you'll have an increased awareness of the various attacks and the techniques to secure your ML systems effectively.

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    O autorach ebooka

    John Paul Mueller jest wolnym strzelcem i redaktorem technicznym. Napisał 104 książki i ponad 600 artykułów o różnorodnej tematyce — od sieci po sztuczną inteligencję, od zarządzania bazami danych po inne obszary programowania. Jest konsultantem, przygotowuje różnego rodzaju egzaminy certyfikacyjne. Ma własną witrynę internetową pod adresem http://johnmuellerbooks.com

    Rod Stephens has been a software developer, consultant, instructor, and author. He has written more than 30 books and 250 magazine articles covering such topics as three-dimensional graphics, algorithms, database design, software engineering, interview puzzles, C#, and Visual Basic. Rod's popular C# Helper and VB Helper websites receive millions of hits per year and contain thousands of tips, tricks, and example programs for C# and Visual Basic developers.

    John Paul Mueller, Rod Stephens - pozostałe książki

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