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You're reading from  50 Algorithms Every Programmer Should Know - Second Edition

Product typeBook
Published inSep 2023
PublisherPackt
ISBN-139781803247762
Edition2nd Edition
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Author (1)
Imran Ahmad
Imran Ahmad
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Imran Ahmad

Imran Ahmad has been a part of cutting-edge research about algorithms and machine learning for many years. He completed his PhD in 2010, in which he proposed a new linear programming-based algorithm that can be used to optimally assign resources in a large-scale cloud computing environment. In 2017, Imran developed a real-time analytics framework named StreamSensing. He has since authored multiple research papers that use StreamSensing to process multimedia data for various machine learning algorithms. Imran is currently working at Advanced Analytics Solution Center (A2SC) at the Canadian Federal Government as a data scientist. He is using machine learning algorithms for critical use cases. Imran is a visiting professor at Carleton University, Ottawa. He has also been teaching for Google and Learning Tree for the last few years.
Read more about Imran Ahmad

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Case study: fraud detection using SNA

Introduction

Humans are inherently social, and their behavior often reflects the company they keep. In the realm of fraud analytics, a principle called “homophily” signifies the likelihood of individuals having associations based on shared attributes or behaviors. A homophilic network, for instance, might comprise people from the same hometown, university, or with shared hobbies. The underlying principle is that individuals’ behavior, including fraudulent activity, might be influenced by their immediate connections. This is also sometimes referred to as “guilt by association.”

What is fraud in this context?

In the context of this case study, fraud refers to deceptive activities that may include impersonation, credit card theft, fake check submission, or any other illicit activities that can be represented and analyzed in a network of relationships. In an effort to understand the process, let’...

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50 Algorithms Every Programmer Should Know - Second Edition
Published in: Sep 2023Publisher: PacktISBN-13: 9781803247762

Author (1)

author image
Imran Ahmad

Imran Ahmad has been a part of cutting-edge research about algorithms and machine learning for many years. He completed his PhD in 2010, in which he proposed a new linear programming-based algorithm that can be used to optimally assign resources in a large-scale cloud computing environment. In 2017, Imran developed a real-time analytics framework named StreamSensing. He has since authored multiple research papers that use StreamSensing to process multimedia data for various machine learning algorithms. Imran is currently working at Advanced Analytics Solution Center (A2SC) at the Canadian Federal Government as a data scientist. He is using machine learning algorithms for critical use cases. Imran is a visiting professor at Carleton University, Ottawa. He has also been teaching for Google and Learning Tree for the last few years.
Read more about Imran Ahmad