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Machine Learning Applications for Accounting Disclosure and Fraud Detection

Disclosure and Fraud Detection is a crucial reference work that uses machine learning techniques in accounting disclosure and identifies;

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Fair Value Accounting Fraud

Fraud risk checklist that you can put to immediate use Practical detection techniques useful for auditors, investigators and others who rely on;

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Empowering Artificial Intelligence Through Machine Learning

learning for credit card fraud detection, using artificial intelligence in education using gaming and automatization with courses and outcomes;

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Guide To Forensic Accounting Investigation

the necessary practical aids, case examples, and skills for identifying situations that call for extended fraud detection procedures.;

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Practical Machine Learning - A New Look at Anomaly Detection

Anomaly detection is the detective work of machine learning: finding the unusual, catching the fraud, discovering strange activity in large;

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Network Anomaly Detection

security, credit card and insurance fraud detection, and military surveillance for enemy activities. Network Anomaly Detection: A Machine Learning;

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Machine Learning in Java

to fraud, anomaly, and outlier detection Experiment with deep learning concepts and algorithms Write your own activity recognition model for;

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Fraud in Financial Statements

fraud, a topical and increasingly challenging area for financial accounting, business, and the law. Evidence shows that accounting anomalies;

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Fraud in Financial Statements

fraud, a topical and increasingly challenging area for financial accounting, business, and the law. Evidence shows that accounting anomalies;

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Deep Learning

detection * Experiment with deep learning concepts, algorithms, and the toolbox for deep learning * Select and split data sets into training, test;

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Corporate Fraud

This book provides a step-by-step guide to detecting fraud and sets out the most effective counter-measures. Written for the non-specialist;

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Apache Spark Machine Learning Blueprints

Apache Spark and R to fit your analytical needs in customer research, fraud detection, risk analytics, and recommendation engine development;

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The Handbook of Fraud Deterrence

The Handbook of Fraud Deterrence encompasses the applicable professional standards and common applications for forensic accounting, fraud;

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Data Science on AWS

Amazon AI and ML stack to real-world use cases for natural language processing, computer vision, fraud detection, conversational devices, and;

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Accounting Fraud

Scandals relating to manipulation and fraud have dominated much of the history of business and the accounting profession in America since;

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Machine Learning and Data Science Blueprints for Finance From Building Trading Strategies to RoboAdvisors Using Python

models for credit default risk prediction, fraud detection, and trading strategies Dimensionality reduction techniques with case studies;

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Deep Learning with Structured Data

Most businesses are far more interested in accurate forecasting and fraud detection using their existing structured datasets than;

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Conformal Prediction for Reliable Machine Learning

financial risk prediction. Conformal Predictions for Reliable Machine Learning: Theory, Adaptations and Applications captures the basic theory;

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Fraud Analytics Using Descriptive Predic

Techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution. Early detection is a key factor;

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Beginning Anomaly Detection Using Python-Based Deep Learning

statistical and traditional machine learning methods for anomaly detection using Scikit-Learn in Python, the book then provides an introduction to;

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Machine Learning Forensics for Law Enforcement, Security, and Intelligence

interrogate the evidence. This powerful data is indispensable for fraud detection, cybersecurity, competitive counterintelligence, and corporate and;

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Machine Learning and Cognitive Science Applications in Cyber Security

variety of sources have been exposed to possible corruption and hacking. Machine learning, artificial intelligence, predictive analytics, and;

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State of the Art in Neural Networks and Their Applications

learning approaches for the detection of renal, retinal, breast, skin, and dental abnormalities and more. Includes applications of neural;

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Machine Learning and Security

explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine;

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Machine Learning for Biometrics

Machine Learning for Biometrics: Concepts, Algorithms and Applications highlights the fundamental concepts of machine learning;

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When Numbers Don't Add Up

comprehensive exploration of the motivations for accounting fraud and a growing realization that Dark Triad (psychopathy, narcissism, and;

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Machine Learning in Radiation Oncology

individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and;

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