Machine Learning Security Principles by John Paul Mueller
As hackers come up with new ways to mangle or misdirect data in nearly undetectable ways to obtain access, skew calculations, and modify outcomes. Machine Learning Security Principles helps you understand hacker motivations and techniques in an easy-to-understand way.
John Paul Mueller is a seasoned author and technical editor. He has writing in his blood, having produced 121 books and more than 600 articles to date. The topics range from networking to artificial intelligence and from database management to heads-down programming. Some of his current books include discussions of data science, machine learning, and algorithms. He also writes about computer languages such as C++, C#, and Python. His technical editing skills have helped more than 70 authors refine the content of their manuscripts. John has provided technical editing services to a variety of magazines, performed various kinds of consulting, and he writes certification exams.
| SKU | Unavailable |
| ISBN 13 | 9781804618851 |
| ISBN 10 | 1804618853 |
| Title | Machine Learning Security Principles |
| Author | John Paul Mueller |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Packt Publishing Limited |
| Year published | 2022-12-30 |
| Number of pages | 450 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |