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

Product type Paperback

Published in Sep 2023

Publisher Packt

ISBN-13 9781803247762

Length 538 pages

Edition 2nd Edition

Languages

Processing

Tools

Processing

Concepts

Data Structures and Algorithms

Author (1):

Imran Ahmad

View More author details

Table of Contents (22) Chapters

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 recommendation systems

Recommendation systems are powerful tools, initially crafted by researchers but now widely adopted in commercial settings, that predict items a user might find appealing. Their ability to deliver personalized item suggestions makes them an invaluable asset, especially in the digital shopping landscape.

When used in e-commerce applications, recommendation engines use sophisticated algorithms to improve the shopping experience for shoppers, allowing service providers to customize products according to the preferences of the users.

A classic example of the significance of these systems is the Netflix Prize challenge in 2009. Netflix, aiming to refine its recommendation algorithm, offered a whopping $1 million prize for any team that could enhance its current recommendation system, Cinematch, by 10%. This challenge saw participation from researchers globally, with BellKor’s Pragmatic Chaos team emerging as the winner. Their achievement...