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40 Algorithms Every Programmer Should Know

You're reading from   40 Algorithms Every Programmer Should Know Hone your problem-solving skills by learning different algorithms and their implementation in Python

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Product type Paperback
Published in Jun 2020
Publisher Packt
ISBN-13 9781789801217
Length 382 pages
Edition 1st Edition
Languages
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Author (1):
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Imran Ahmad Imran Ahmad
Author Profile Icon Imran Ahmad
Imran Ahmad
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Table of Contents (19) Chapters Close

Preface 1. Section 1: Fundamentals and Core Algorithms
2. Overview of Algorithms FREE CHAPTER 3. Data Structures Used in Algorithms 4. Sorting and Searching Algorithms 5. Designing Algorithms 6. Graph Algorithms 7. Section 2: Machine Learning Algorithms
8. Unsupervised Machine Learning Algorithms 9. Traditional Supervised Learning Algorithms 10. Neural Network Algorithms 11. Algorithms for Natural Language Processing 12. Recommendation Engines 13. Section 3: Advanced Topics
14. Data Algorithms 15. Cryptography 16. Large-Scale Algorithms 17. Practical Considerations 18. Other Books You May Enjoy

Case study – fraud analytics

Let's look at how we can use SNA to detect fraud. With humans being social animals, human behavior is said to be affected by the people that you are surrounded by. The word homophily has been coined to represent the effect their social network has on a person. Extending this concept, a homophilic network is a group of people who are likely to be associated with each other due to some common factor; for example, having the same origin or hobbies, being part of the same gang or the same university, or some combination of other factors.

If we want to analyze fraud in a homophilic network, we can take advantage of the relationships between the person under investigation and other people in the network, whose risk of involvement in fraud has already been carefully calculated. Flagging a person due to their company is sometimes also...

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