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

Understanding ethics and algorithms

Algorithmic ethics, also known as computational ethics, delves into the moral dimensions of algorithms. This crucial domain aims to ensure that machines operating on these algorithms uphold ethical standards. The development and deployment of algorithms may inadvertently foster unethical outcomes or biases. Crafting algorithms poses a challenge in anticipating their full range of ethical repercussions. When we discuss large-scale algorithms in this context, we refer to those processing vast volumes of data. However, the complexity is magnified when multiple users or designers contribute to an algorithm, introducing varied human biases. The overarching goal of algorithmic ethics is to spotlight and address concerns arising in these areas:

Bias and discrimination: There are many factors that can affect the quality of the solutions created by algorithms. One of the major concerns is unintentional and algorithmic bias. The reason may be the...