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50 Algorithms Every Programmer Should Know

You're reading from   50 Algorithms Every Programmer Should Know Tackle computer science challenges with classic to modern algorithms in machine learning, software design, data systems, and cryptography

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Product type Paperback
Published in Sep 2023
Publisher Packt
ISBN-13 9781803247762
Length 538 pages
Edition 2nd 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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Toc

Table of Contents (22) Chapters Close

Preface 1. Section 1: Fundamentals and Core Algorithms FREE CHAPTER
2. Overview of Algorithms 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. Understanding Sequential Models 13. Advanced Sequential Modeling Algorithms 14. Section 3: Advanced Topics
15. Recommendation Engines 16. Algorithmic Strategies for Data Handling 17. Cryptography 18. Large-Scale Algorithms 19. Practical Considerations 20. Other Books You May Enjoy
21. Index

Introducing network analysis theory

Network analysis allows us to delve into data that’s interconnected, presenting it in the form of a network. It involves studying and employing methodologies to examine data that’s arranged in this network format. Here, we’ll break down the core elements and concepts related to network analysis.

At the heart of a network lies the “vertex,” serving as the fundamental unit. Picture a network as a web; vertices are the points of this web, while the links connecting them represent relationships between different entities under study. Notably, different relationships can exist between two vertices, implying that edges can be labeled to denote various kinds of relationships. Imagine two people being connected as “friends” and “colleagues”; both are different relationships but link the same individuals.

To fully harness the potential of network analysis, it’s vital to gauge the...

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