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Beschreibung
This book is a comprehensive guide designed for professionals in high-risk sectors, bridging the gap between traditional auditing methods and the modern digital landscape. This book offers innovative solutions, practical Python coding exercises, and real-world scenarios, equipping readers with invaluable insights into fraud analytics. Tailored for internal auditors, data scientists, and analysts, it's an essential resource for navigating the complexities of fraud in the digital era.
Data Science and Machine Learning Techniques for Detecting Fraud in the Digital Age
Details
| Verlag | Springer International Publishing |
| Ersterscheinung | 17. Juli 2026 |
| Maße | 21 cm x 14.8 cm |
| Gewicht | 811 Gramm |
| Format | Hardcover |
| ISBN-13 | 9783032160225 |
| Seiten | 490 |
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