Advanced Credit Card Fraud Detection with Hybrid Optimization and Deep Learning: A Comprehensive Guide to Model Design, Optimization, and Performance Enhancement - Couverture souple

Kolli, Dr. Chandra Sekhar

Couverture souple

ISBN 10 : 9999330045 ISBN 13 : 9789999330046

Editeur : Eliva Press, 2025

Synopsis

In today’s fast-paced digital economy, credit card fraud poses one of the greatest challenges to financial security. Advanced Credit Card Fraud Detection with Hybrid Optimization and Deep Learning bridges the gap between cutting-edge research and practical implementation, offering a comprehensive guide for students, researchers, and professionals. This book explores the integration of hybrid optimization techniques with deep recurrent neural networks (RNNs) to create high-performance fraud detection systems. Through clear explanations, mathematical foundations, and real-world case studies, it demonstrates how combining feature selection, model tuning, and sequential deep learning can dramatically improve detection accuracy while reducing false alarms.   Readers will learn: The fundamentals of credit card fraud patterns and detection challenges Hybrid optimization algorithms for feature engineering and model enhancement Deep RNN architectures, including LSTM and GRU, for sequential data analysis End-to-end implementation strategies using real datasets Performance evaluation and deployment in real-world financial systems Whether you are an academic exploring AI in finance, a data scientist building detection models, or a security professional safeguarding transactions, this book provides the tools and knowledge to stay ahead in the evolving battle against financial fraud.

Détails de l'édition

• Éditeur: Eliva Press
• Date d'édition: 2025
• Langue: anglais
• ISBN 10: 9999330045
• ISBN 13: 9789999330046
• Reliure: Broché
• Nombre de pages: 229
• Coordonnées du fabricant: non disponible
• Personne responsable: gpsr@libri.de; gpsr@libri.de; ; Europaallee 1; Bad Hersfeld; 36244; Allemagne