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Data Science and Machine Learning Techniques for Detecting Fraud in the Digital Age
Louise Reader
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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.
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PDF : format reprenant la maquette originale du livre ; lecture recommandée sur ordinateur et tablette EPUB : format de texte repositionnable ; lecture sur tous supports (ordinateur, tablette, smartphone, liseuse)
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Abdelrahim Aqqad has more than 15 years of experience as a Chief Internal Auditor alongside expertise in governance, risk management, internal control, and process re-engineering. He has authored numerous articles and spoken at various conferences, establishing himself as a thought leader in fraud analytics and risk management.
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