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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

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

When is linear regression used?

Linear regression is used to solve many real-world problems, including the following:

Sales forecasting
Predicting optimum product prices
Quantifying the causal relationship between an event and the response, such as in clinical drug trials, engineering safety tests, or marketing research
Identifying patterns that can be used to forecast future behavior, given known criteria—for example, predicting insurance claims, natural disaster damage, election results, and crime rates

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Authors (1)

Imran Ahmad

Imran Ahmad

Imran Ahmad is the author of the “50 Algorithms every programmer should know”. He 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.

See other products by Imran Ahmad

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